|
Aller au contenu
|
Interno |
Passing Juice |
|
Prof. Stephan ROBERT-NICOUD, PhD
|
Externo |
Passing Juice |
|
Recherche
|
Interno |
Passing Juice |
|
Team
|
Externo |
Passing Juice |
|
Research
|
Externo |
Passing Juice |
|
Research Projects
|
Externo |
Passing Juice |
|
Gestion des situations de crises sanitaires
|
Externo |
Passing Juice |
|
Système d’Intelligence Artificielle – Régulation Médicale des Urgences (SIA-REMU)
|
Externo |
Passing Juice |
|
Adaptive Tuning of Neural Networks Parameters for Time Series Prediction
|
Externo |
Passing Juice |
|
Active Learning and Autoencoders in Banking Fraud Detection (ALEA)
|
Externo |
Passing Juice |
|
Blockchain and Cryptocurrencies
|
Externo |
Passing Juice |
|
Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning (OPERATE)
|
Externo |
Passing Juice |
|
WhiteBoard Seminars
|
Externo |
Passing Juice |
|
Jobs
|
Externo |
Passing Juice |
|
Engineering
|
Externo |
Passing Juice |
|
Student Projects
|
Externo |
Passing Juice |
|
Study abroad Students Testamonials
|
Externo |
Passing Juice |
|
Publications
|
Externo |
Passing Juice |
|
AI – Resources
|
Externo |
Passing Juice |
|
Teaching
|
Externo |
Passing Juice |
|
Doctoral Classes
|
Externo |
Passing Juice |
|
Analysis of Sequential Data
|
Externo |
Passing Juice |
|
Apprentissage supervisé (APV)
|
Externo |
Passing Juice |
|
Introduction à la science des données (ISD)
|
Externo |
Passing Juice |
|
Apprentissage par Réseaux de Neurones artificiels (ARN)
|
Externo |
Passing Juice |
|
Previous courses
|
Externo |
Passing Juice |
|
Summer University
|
Externo |
Passing Juice |
|
2020 and 2021 Summer University
|
Externo |
Passing Juice |
|
2019 Summer University
|
Externo |
Passing Juice |
|
2018 Summer University
|
Externo |
Passing Juice |
|
SU’18-CSCS, Pictures
|
Externo |
Passing Juice |
|
2017 Summer University
|
Externo |
Passing Juice |
|
2016 Summer University
|
Externo |
Passing Juice |
|
2015 Summer University
|
Externo |
Passing Juice |
|
2014 Summer University
|
Externo |
Passing Juice |
|
2013 Summer University
|
Externo |
Passing Juice |
|
News (press)
|
Externo |
Passing Juice |
|
Private
|
Externo |
Passing Juice |
|
Bistro du Marronnier
|
Externo |
Passing Juice |
|
Chestnut Tree Videos
|
Externo |
Passing Juice |
|
Permaculture
|
Externo |
Passing Juice |
|
Family
|
Externo |
Passing Juice |
|
Reading Group in Contemporary Evangelical Philosophy
|
Externo |
Passing Juice |
|
Videos-teaching
|
Externo |
Passing Juice |
|
Mérites ponliers
|
Externo |
Passing Juice |
|
Contact
|
Externo |
Passing Juice |
|
Gestion des situations de crises sanitaires (GESICA)
|
Externo |
Passing Juice |
|
SCHOOL OF ENGINEERING AND MANAGEMENT SCHEDULING
|
Externo |
Passing Juice |
|
Active Learning and Autoencoders in Banking Fraud Detection (ALEA)
|
Externo |
Passing Juice |
|
Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning (OPERATE)
|
Externo |
Passing Juice |
|
Advanced topics in theorem proving
|
Externo |
Passing Juice |
|
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
|
Externo |
Passing Juice |
|
miniCTX: Neural Theorem Proving with (Long-)Contexts
|
Externo |
Passing Juice |
|
Lean-STaR: Learning to Interleave Thinking and Proving
|
Externo |
Passing Juice |
|
ImProver: Agent-Based Automated Proof Optimization
|
Externo |
Passing Juice |
|
AI’s Models of the World, and Ours | Theoretically Speaking
|
Externo |
Passing Juice |
|
Do Mathematicians Need Computers?
|
Externo |
Passing Juice |
|
LMs for Autoformalization+Theorem Proving
|
Externo |
Passing Juice |
|
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
|
Externo |
Passing Juice |
|
Autoformalization with Large Language Models
|
Externo |
Passing Juice |
|
Autoformalizing Euclidean Geometry
|
Externo |
Passing Juice |
|
New Simple Optimizer: Muon
|
Externo |
Passing Juice |
|
AlphaProof, When RL meets formal maths
|
Externo |
Passing Juice |
|
AI achieves silver-medal standard solving International Mathematical Olympiad problems
|
Externo |
Passing Juice |
|
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
|
Externo |
Passing Juice |
|
The Future of Mathematics?
|
Externo |
Passing Juice |
|
Building the Mathematical Library of the Future
|
Externo |
Passing Juice |
|
Mystères mathématiques d’intelligences pas si artificielles
|
Externo |
Passing Juice |
|
Le pouvoir de la symétrie
|
Externo |
Passing Juice |
|
Realizing Nakamoto’s Dream: One-Time Signatures, Garbled Circuits & Zero-Knowledge Proofs
|
Externo |
Passing Juice |
|
Where is Mathematics Going?
|
Externo |
Passing Juice |
|
Multimodal Agent
|
Externo |
Passing Juice |
|
OSWORLD: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
|
Externo |
Passing Juice |
|
AGUVIS: Unified Pure Vision Agents For Autonomous GUI Interaction
|
Externo |
Passing Juice |
|
Multimodal Autonomous Agents
|
Externo |
Passing Juice |
|
Mind2Web: Towards a Generalist Agent for the Web
|
Externo |
Passing Juice |
|
WebArena: A Realistic Web Environment for Building Autonomous Agents
|
Externo |
Passing Juice |
|
VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
|
Externo |
Passing Juice |
|
Tree Search for Language Model Agent
|
Externo |
Passing Juice |
|
Coding Agents and AI for Vulnerability Detection
|
Externo |
Passing Juice |
|
Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities
|
Externo |
Passing Juice |
|
From Naptime to Big Sleep: Using Large Language Models To Catch Vulnerabilities In Real-World Code
|
Externo |
Passing Juice |
|
Open Training Recipes for Reasoning in Language Models,
|
Externo |
Passing Juice |
|
Tulu 3: Pushing Frontiers in Open Language Model Post-Training
|
Externo |
Passing Juice |
|
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback
|
Externo |
Passing Juice |
|
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs
|
Externo |
Passing Juice |
|
Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization
|
Externo |
Passing Juice |
|
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
|
Externo |
Passing Juice |
|
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
|
Externo |
Passing Juice |
|
Learning to Self-Improve & Reason with LLMs
|
Externo |
Passing Juice |
|
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
|
Externo |
Passing Juice |
|
Iterative Reasoning Preference Optimization
|
Externo |
Passing Juice |
|
Chain-of-Verification Reduces Hallucination in Large Language Models
|
Externo |
Passing Juice |
|
Spectral Zeta Function of Graphs and the Riemann Zeta Function
|
Externo |
Passing Juice |
|
Inference-Time Techniques for LLM Reasoning
|
Externo |
Passing Juice |
|
L’interview d’Hugo Duminil-Copin, médaillé Fields
|
Externo |
Passing Juice |
|
David Pouapre
|
Externo |
Passing Juice |
|
Launch of the Gesica project
|
Externo |
Passing Juice |
|
BioTech Campus
|
Externo |
Passing Juice |
|
Prof. Hugo Duminil Copain (Fields Medalist 2022)
|
Externo |
Passing Juice |
|
Post
|
Externo |
Passing Juice |
|
Robert Mardini,
|
Externo |
Passing Juice |
|
HUG
|
Externo |
Passing Juice |
|
ICRC (International Comettee of the Red Cross)
|
Externo |
Passing Juice |
|
LLM Scientist Toolkit, Key Insights from NeurIPS
|
Externo |
Passing Juice |
|
Official interview
|
Externo |
Passing Juice |
|
Sequence to Sequence Learning with Neural Networks
|
Externo |
Passing Juice |
|
, Evaluating Large Language Models – Principles, Approaches, and Applications
|
Externo |
Passing Juice |
|
Graph Learning: Principles, Challenges, and Open Directions
|
Externo |
Passing Juice |
|
Physics of Language Models
|
Externo |
Passing Juice |
|
CLIMB talk with Martin Wainwright
|
Externo |
Passing Juice |
|
Mastering LLM Inference Optimization From Theory to Cost Effective Deployment
|
Externo |
Passing Juice |
|
Diffusion Models
|
Externo |
Passing Juice |
|
GAN, Video, point Cloud
|
Externo |
Passing Juice |
|
Vision Transformer
|
Externo |
Passing Juice |
|
Long-Context LLMs
|
Externo |
Passing Juice |
|
Transformer and LLM
|
Externo |
Passing Juice |
|
Mathematical Discoveries from program Search with Large Language Models
|
Externo |
Passing Juice |
|
How should we evaluate long-context language models
|
Externo |
Passing Juice |
|
« What robots have taught me about machine learning »
|
Externo |
Passing Juice |
|
Abide by the law and follow the flow: conservation laws for gradient flows
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Causal Imputation and Causal Disentanglement
|
Externo |
Passing Juice |
|
Optimal Quantile Estimation for Streams
|
Externo |
Passing Juice |
|
Data Contribution Estimation for Machine Learning
|
Externo |
Passing Juice |
|
Do You Prefer Learning with Preferences?
|
Externo |
Passing Juice |
|
Transformers for Bootstrapperd Amplitudes,
|
Externo |
Passing Juice |
|
Chaining: a long story (Abel lecture)
|
Externo |
Passing Juice |
|
Nobel Prize lectures in physics
|
Externo |
Passing Juice |
|
Sparsification of Gaussian Processes
|
Externo |
Passing Juice |
|
Inverse Reinforcement Learning
|
Externo |
Passing Juice |
|
Learning-Based Solutions for Inverse Problems
|
Externo |
Passing Juice |
|
The Era of 1-bit LLMs-All Large Language Models are in 1.58 Bits
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
The Many Faces of Responsible AI
|
Externo |
Passing Juice |
|
Pretrained diffusion is all we need: a journey beyond training distribution
|
Externo |
Passing Juice |
|
Heavy Tails in ML: Structure, Stability, Dynamics
|
Externo |
Passing Juice |
|
Unsupervised Pre-Training:Contrastive Learning
|
Externo |
Passing Juice |
|
class link
|
Externo |
Passing Juice |
|
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Scaling Data-Constrained Language Models (at NeurIPS)
|
Externo |
Passing Juice |
|
long version
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Are Emergent Abilities of Large Language Models a Mirage?
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Statistical Applications of Wasserstein Gradient Flows
|
Externo |
Passing Juice |
|
Pareto Invariant Risk Minimization: Towards Mitigating The Optimization Dilemma in Out-of-Distribution Generalization
|
Externo |
Passing Juice |
|
Artificial Intelligence, Ethics, and a Right to a Human Decision
|
Externo |
Passing Juice |
|
Analyzing Transfer Learning Bounds through Distributional Robustness
|
Externo |
Passing Juice |
|
Designing High-Dimensional Closed-Loop Optimal Control Using Deep Neural Networks
|
Externo |
Passing Juice |
|
Climate modeling with AI: Hype or Reality?
|
Externo |
Passing Juice |
|
Generative Models and Physical Processes
|
Externo |
Passing Juice |
|
Quantifying causal influence in time series and beyond
|
Externo |
Passing Juice |
|
Reasoning and Abstraction as Challenges for AI
|
Externo |
Passing Juice |
|
Steering AI for the Public Good: A Dialogue for the Future
|
Externo |
Passing Juice |
|
Topological Modeling of Complex Data
|
Externo |
Passing Juice |
|
Transformers United
|
Externo |
Passing Juice |
|
Variational Autoencoder
|
Externo |
Passing Juice |
|
Could a Large Language Model be Conscious?
|
Externo |
Passing Juice |
|
Transformers and Pretraining
|
Externo |
Passing Juice |
|
Introduction to self-attention and transformers
|
Externo |
Passing Juice |
|
GPT-3 & Beyond
|
Externo |
Passing Juice |
|
Reinforcement Learning 10 (Classic Games Case Study)
|
Externo |
Passing Juice |
|
How to increase certainty in predictive modeling
|
Externo |
Passing Juice |
|
, Reinforcement Learning 8 (Advanced Topics in Deep RL)
|
Externo |
Passing Juice |
|
Reinforcement Learning 7 (Planning and Models)
|
Externo |
Passing Juice |
|
Reinforcement Learning 6 (Policy Gradients and Actor Critics)
|
Externo |
Passing Juice |
|
Reinforcement Learning 4 (Model-Free Prediction and Control)
|
Externo |
Passing Juice |
|
Offline Reinforcement Learning
|
Externo |
Passing Juice |
|
Reinforcement Learning 2 (Exploration and Exploitation)
|
Externo |
Passing Juice |
|
Reinforcement Learning 1
|
Externo |
Passing Juice |
|
RLbook2020
|
Externo |
Passing Juice |
|
Introduction to Algebraic Topology
|
Externo |
Passing Juice |
|
Signal Recovery with Generative Priors
|
Externo |
Passing Juice |
|
Learning-Based Low-Rank Approximations
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
General graph problems with neural networks
|
Externo |
Passing Juice |
|
The Transformer Network for the Traveling Salesman Problem
|
Externo |
Passing Juice |
|
Artificial Intelligence in Acute Medecine, From theory to applications
|
Externo |
Passing Juice |
|
Attention, Learn to Solve Routing Problems!
|
Externo |
Passing Juice |
|
Why Did Quantum Entanglement Win the Nobel Prize in Physics?
|
Externo |
Passing Juice |
|
Sixty Symbols – Spooky Action at a Distance (Bell’s Inequality)
|
Externo |
Passing Juice |
|
EigenGame PCA as a Nash Equilibrium
|
Externo |
Passing Juice |
|
Deep Semi-Supervised Anomaly Detection
|
Externo |
Passing Juice |
|
Discovering faster matrix multiplication algorithms with reinforcement learning
|
Externo |
Passing Juice |
|
Compressing Variational Bayes
|
Externo |
Passing Juice |
|
From Machine Learning to Autonomous Intelligence
|
Externo |
Passing Juice |
|
Diffusion Probabilistic Models
|
Externo |
Passing Juice |
|
Attention and Memory in Deep Learning
|
Externo |
Passing Juice |
|
Transformers and Self-Attention
|
Externo |
Passing Juice |
|
Ensuring Safety in Online Reinforcement Learning by Leveraging Offline Data
|
Externo |
Passing Juice |
|
Geometric Deep Learning: The Erlangen Programme of ML
|
Externo |
Passing Juice |
|
The Devil is in the Tails and Other Stories of Interpolation
|
Externo |
Passing Juice |
|
Gaussian multiplicative chaos: applications and recent developments
|
Externo |
Passing Juice |
|
Statistical mechanics arising from random matrix theory
|
Externo |
Passing Juice |
|
Stop Explaining Black Box Machine Learning Models
|
Externo |
Passing Juice |
|
Network Calculus
|
Externo |
Passing Juice |
|
Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
|
Externo |
Passing Juice |
|
Generation and Simulation of Synthetic Datasets with Copulas
|
Externo |
Passing Juice |
|
arXiv:2203.17250
|
Externo |
Passing Juice |
|
Combining Reinforcement Learning & Constraint Programming for Combinator…
|
Externo |
Passing Juice |
|
Deep Reinforcement Learning at the Edge of the Statistical Precipice
|
Externo |
Passing Juice |
|
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
|
Externo |
Passing Juice |
|
I Can’t Believe Latent Variable Models Are Not Better
|
Externo |
Passing Juice |
|
From System 1 Deep Learning to System 2 Deep Learning
|
Externo |
Passing Juice |
|
Latent Dirichlet Allocation
|
Externo |
Passing Juice |
|
Online Learning for Latent Dirichlet Allocation
|
Externo |
Passing Juice |
|
On the Expressivity of Markov Reward
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Continuous Time Dynamic Programming — The Hamilton-Jacobi-Bellman Equation
|
Externo |
Passing Juice |
|
Computational Barriers in Statistical Estimation and Learning
|
Externo |
Passing Juice |
|
Offline Deep Reinforcement Learning Algorithms
|
Externo |
Passing Juice |
|
Infusing Physics and Structure into Machine
|
Externo |
Passing Juice |
|
Robust Predictable Control
|
Externo |
Passing Juice |
|
web page
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Recent Advances in Integrating Machine Learning and Combinatorial Optimization – Tutorial at AAAI-21
|
Externo |
Passing Juice |
|
Attention and Transformer Networks
|
Externo |
Passing Juice |
|
Yes, Generative Models Are The New Sparsity
|
Externo |
Passing Juice |
|
The Knockoffs Framework: New Statistical Tools for Replicable Selections
|
Externo |
Passing Juice |
|
Compositional Dynamics Modeling for Physical Inference and Control
|
Externo |
Passing Juice |
|
Safe and Efficient Exploration in Reinforcement Learning
|
Externo |
Passing Juice |
|
Luis von Ahn
|
Externo |
Passing Juice |
|
Contrastive Learning: A General Self-supervised Learning Approach
|
Externo |
Passing Juice |
|
https://arxiv.org/abs/2004.11362
|
Externo |
Passing Juice |
|
Adversarial Robustness – Theory and Practice
|
Externo |
Passing Juice |
|
Recent Developments in Over-parametrized Neural Networks
|
Externo |
Passing Juice |
|
Feedback Control Perspectives on Learning
|
Externo |
Passing Juice |
|
Self-Supervised Learning & World Models
|
Externo |
Passing Juice |
|
Theoretical Foundations of Graph Neural Networks
|
Externo |
Passing Juice |
|
Deep Implicit Layers
|
Externo |
Passing Juice |
|
Bayesian Deep Learning and Probabilistic Model Construction
|
Externo |
Passing Juice |
|
Learning Ising Models from One, Ten or a Thousand Samples
|
Externo |
Passing Juice |
|
Deconstructing the Blockchain to Approach Physical Limits
|
Externo |
Passing Juice |
|
Federated Learning and Analytics at Google and Beyond
|
Externo |
Passing Juice |
|
Equivariant Networks and Natural Graph Networks
|
Externo |
Passing Juice |
|
1
|
Externo |
Passing Juice |
|
2
|
Externo |
Passing Juice |
|
3
|
Externo |
Passing Juice |
|
4
|
Externo |
Passing Juice |
|
Machine Learning with Signal Processing
|
Externo |
Passing Juice |
|
A Function Approximation of Perspective on Sensory Representations
|
Externo |
Passing Juice |
|
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
|
Externo |
Passing Juice |
|
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
|
Externo |
Passing Juice |
|
On Exact Computation with an Infinitely Wide Neural Net
|
Externo |
Passing Juice |
|
Spectrum Dependent Learning Curves in Kernel Regression and Wide
|
Externo |
Passing Juice |
|
Hopfield Networks in 2021
|
Externo |
Passing Juice |
|
Influence: Using Disentangled Representations to Audit Model Predictions
|
Externo |
Passing Juice |
|
Offline Reinforcement Learning
|
Externo |
Passing Juice |
|
Stanford Seminar (part 2) – Information Theory of Deep Learning
|
Externo |
Passing Juice |
|
New Theory Cracks Open the Black Box of Deep Learning
|
Externo |
Passing Juice |
|
Computer vision: who is harmed and who benefits?
|
Externo |
Passing Juice |
|
Smart Interfaces for Human-Centered AI
|
Externo |
Passing Juice |
|
Anthropological/Artificial Intelligence & the HAI
|
Externo |
Passing Juice |
|
Faception
|
Externo |
Passing Juice |
|
HireVue
|
Externo |
Passing Juice |
|
Our Data Bodies
|
Externo |
Passing Juice |
|
Network Telemetry and Analytics for tomorrows Zero Touch Operation Network
|
Externo |
Passing Juice |
|
Representation Learning Without Labels
|
Externo |
Passing Juice |
|
Active Learning: From Theory to Practice
|
Externo |
Passing Juice |
|
Stanford Seminar – Machine Learning for Creativity, Interaction, and Inclusion,
|
Externo |
Passing Juice |
|
pdf
|
Externo |
Passing Juice |
|
LambdaNetworks: Modeling long-range Interactions without Attention (Paper Explained, ICLR 2021 submission)
|
Externo |
Passing Juice |
|
Artificial Stupidity: The New AI and the Future of Fintech
|
Externo |
Passing Juice |
|
LSTM is dead. Long Live Transformers!
|
Externo |
Passing Juice |
|
LSTM paper
|
Externo |
Passing Juice |
|
LSTM Diagrams- Understanding LSTM
|
Externo |
Passing Juice |
|
Attention is all you need
|
Externo |
Passing Juice |
|
Illustrated Attention
|
Externo |
Passing Juice |
|
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
|
Externo |
Passing Juice |
|
Deep contextualized word representations
|
Externo |
Passing Juice |
|
huggingface/transformers
|
Externo |
Passing Juice |
|
Machine Learning Projects Against COVID-19
|
Externo |
Passing Juice |
|
Kernel and Deep Regimes in Overparameterized Learning
|
Externo |
Passing Juice |
|
Energy-based Approaches to Representation Learning,
|
Externo |
Passing Juice |
|
Learnability can be undecidable
|
Externo |
Passing Juice |
|
On Learnability with Computable Learners
|
Externo |
Passing Juice |
|
Generalized Resilience and Robust Statistics
|
Externo |
Passing Juice |
|
Slides
|
Externo |
Passing Juice |
|
Generalized Resilience and Robust Statistics
|
Externo |
Passing Juice |
|
Outlier analysis
|
Externo |
Passing Juice |
|
From Classical Statistics to Modern Machine Learning
|
Externo |
Passing Juice |
|
To Understand Deep Learning We Need to Understand Kernel Learning
|
Externo |
Passing Juice |
|
Kernel Regression Estimate
|
Externo |
Passing Juice |
|
Nearest Neighbor Pattern Classification, Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
|
Externo |
Passing Juice |
|
Overparameterized Neural Networks Can Implement Associative Memory
|
Externo |
Passing Juice |
|
Reconciling modern machine-learning practice and the classical bias–variance trade-off
|
Externo |
Passing Juice |
|
High-dimensional dynamics of generalization error in neural networks
|
Externo |
Passing Juice |
|
Automatic Machine Learning, part 3
|
Externo |
Passing Juice |
|
Slides part 3
|
Externo |
Passing Juice |
|
Slides parts 1-2,
|
Externo |
Passing Juice |
|
Neural Architecture Search: A Survey.
|
Externo |
Passing Juice |
|
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
|
Externo |
Passing Juice |
|
Automatically-Tuned Neural Networks
|
Externo |
Passing Juice |
|
Neural Architecture Search with Reinforcement Learning,
|
Externo |
Passing Juice |
|
An Evolutionary Algorithm that Constructs Recurrent Neural Networks
|
Externo |
Passing Juice |
|
Evolving Neural Networks through Augmenting Topologies
|
Externo |
Passing Juice |
|
Evolving Deep Neural Networks
|
Externo |
Passing Juice |
|
Regularized Evolution for Image Classifier Architecture Search
|
Externo |
Passing Juice |
|
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
|
Externo |
Passing Juice |
|
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
|
Externo |
Passing Juice |
|
Progressive Neural Architecture Search
|
Externo |
Passing Juice |
|
Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search
|
Externo |
Passing Juice |
|
Transfer Learning with Neural AutoML
|
Externo |
Passing Juice |
|
Net2Net: Accelerating Learning via Knowledge Transfer
|
Externo |
Passing Juice |
|
Network Morphism
|
Externo |
Passing Juice |
|
Path-Level Network Transformation for Efficient Architecture Search
|
Externo |
Passing Juice |
|
Efficient Architecture Search by Network Transformation
|
Externo |
Passing Juice |
|
Simple and Efficient Architecture Search for CNNs
|
Externo |
Passing Juice |
|
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
|
Externo |
Passing Juice |
|
Convolutional Neural Fabrics
|
Externo |
Passing Juice |
|
Understanding and Simplifying One-Shot Architecture Search
|
Externo |
Passing Juice |
|
Efficient Neural Architecture Search via Parameter Sharing
|
Externo |
Passing Juice |
|
SMASH: One-Shot Model Architecture Search through HyperNetworks
|
Externo |
Passing Juice |
|
DARTS: Differentiable Architecture Search
|
Externo |
Passing Juice |
|
MnasNet: Platform-Aware Neural Architecture Search for Mobile
|
Externo |
Passing Juice |
|
Selecting Classification Algorithms with Active Testing
|
Externo |
Passing Juice |
|
Speeding up algorithm selection using average ranking and active testing by introducing runtime
|
Externo |
Passing Juice |
|
Learning Hyperparameter Optimization Initializations
|
Externo |
Passing Juice |
|
Hyperparameter Importance Across Datasets
|
Externo |
Passing Juice |
|
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
|
Externo |
Passing Juice |
|
Hyperparameter Search Space Pruning – A New Component for Sequential Model-Based Hyperparameter Optimization
|
Externo |
Passing Juice |
|
Gaussian Processes for Machine Learning
|
Externo |
Passing Juice |
|
Scalable Gaussian process-based transfer surrogates for hyperparameter optimization
|
Externo |
Passing Juice |
|
Scalable Meta-Learning for Bayesian Optimization
|
Externo |
Passing Juice |
|
Book, chapter 1,
|
Externo |
Passing Juice |
|
On bayesian methods for seeking the extremum
|
Externo |
Passing Juice |
|
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
|
Externo |
Passing Juice |
|
Bayesian Optimization with Exponential Convergence
|
Externo |
Passing Juice |
|
Bayesian Optimization in High Dimensions via Random Embeddings
|
Externo |
Passing Juice |
|
Sequential Model-Based Optimization for General Algorithm Configuration
|
Externo |
Passing Juice |
|
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
|
Externo |
Passing Juice |
|
Random Forests
|
Externo |
Passing Juice |
|
Scalable Bayesian Optimization Using Deep Neural Networks
|
Externo |
Passing Juice |
|
Bayesian Optimization with Robust Bayesian Neural Networks
|
Externo |
Passing Juice |
|
Algorithms for Hyper-Parameter Optimization
|
Externo |
Passing Juice |
|
Evolution strategies –A comprehensive introduction
|
Externo |
Passing Juice |
|
The CMA Evolution Strategy: A Tutorial
|
Externo |
Passing Juice |
|
CMA-ES for hyperparameters optimization of neural networks
|
Externo |
Passing Juice |
|
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves
|
Externo |
Passing Juice |
|
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
|
Externo |
Passing Juice |
|
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
|
Externo |
Passing Juice |
|
Learning curve prediction with Bayesian neural networks
|
Externo |
Passing Juice |
|
Multi-Task Bayesian Optimization
|
Externo |
Passing Juice |
|
Freeze-Thaw Bayesian optimization
|
Externo |
Passing Juice |
|
Multi-fidelity Bayesian Optimisation with Continuous Approximations
|
Externo |
Passing Juice |
|
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
|
Externo |
Passing Juice |
|
Github link
|
Externo |
Passing Juice |
|
Hyperband: Bandit-based configuration evaluation for hyperband parameters optimiation
|
Externo |
Passing Juice |
|
Non-stochastic Best Arm Identification and Hyperparameter Optimization
|
Externo |
Passing Juice |
|
Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms
|
Externo |
Passing Juice |
|
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn
|
Externo |
Passing Juice |
|
Efficient and Robust Automated Machine Learning, Auto-sklearn,
|
Externo |
Passing Juice |
|
GitHub link
|
Externo |
Passing Juice |
|
Automating Biomedical Data Science Through Tree-Based Pipeline Optimization
|
Externo |
Passing Juice |
|
Using Knockoffs to Find Important Variables with Statistical Guarantees
|
Externo |
Passing Juice |
|
Learning Noise-Invariant Representations for Robust Speech Recognition
|
Externo |
Passing Juice |
|
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
|
Externo |
Passing Juice |
|
Deep Active Learning for Named Entity Recognition
|
Externo |
Passing Juice |
|
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study
|
Externo |
Passing Juice |
|
Practical Obstacles to Deploying Active Learning
|
Externo |
Passing Juice |
|
Active Learning with Partial Feedback
|
Externo |
Passing Juice |
|
Learning From Noisy Singly-labeled Data
|
Externo |
Passing Juice |
|
Deep Active Learning for Named Entity Recognition
|
Externo |
Passing Juice |
|
What is the Effect of Importance Weighting in Deep Learning?
|
Externo |
Passing Juice |
|
Understanding Neural Networks Through Deep Visualization
|
Externo |
Passing Juice |
|
Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data
|
Externo |
Passing Juice |
|
Stochastic Neural Network with Kronecker Flow
|
Externo |
Passing Juice |
|
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
|
Externo |
Passing Juice |
|
Learning with Differential Privacy
|
Externo |
Passing Juice |
|
Bayes point machines
|
Externo |
Passing Juice |
|
The role of over-parametrization in generalization of neural networks
|
Externo |
Passing Juice |
|
PAC-Bayesian Transportation Bound
|
Externo |
Passing Juice |
|
Probably Approximately Correct Learning
|
Externo |
Passing Juice |
|
A primer on PAC-Bayesian learning
|
Externo |
Passing Juice |
|
Integrating Constraints into Deep Learning Architectures with Structured Layers
|
Externo |
Passing Juice |
|
Convolutional Deep Belief Networksfor Scalable Unsupervised Learning of Hierarchical Representations
|
Externo |
Passing Juice |
|
OptNet: Differentiable Optimization as a Layer in Neural Networks.
|
Externo |
Passing Juice |
|
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver.
|
Externo |
Passing Juice |
|
Neural Ordinary Differential Equations
|
Externo |
Passing Juice |
|
Trellis Networks for Sequence Modeling.
|
Externo |
Passing Juice |
|
Variational Auto Encoders
|
Externo |
Passing Juice |
|
β-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework
|
Externo |
Passing Juice |
|
What is consciousness, and could machines have it?
|
Externo |
Passing Juice |
|
The Consciousness Prior
|
Externo |
Passing Juice |
|
Better Mixing via Deep Representations
|
Externo |
Passing Juice |
|
Independently Controllable Factors
|
Externo |
Passing Juice |
|
On the Computational Utility of Consciousness
|
Externo |
Passing Juice |
|
Self-organizing neural network that discovers surfaces in random-dot stereograms. Nature
|
Externo |
Passing Juice |
|
Rebooting AI
|
Externo |
Passing Juice |
|
Is Optimization the Right Language to Understand Deep Learning?
|
Externo |
Passing Juice |
|
Adversarial Machine Learning
|
Externo |
Passing Juice |
|
Our Mathematical Universe
|
Externo |
Passing Juice |
|
Nobel Lecture: Michel Mayor, Nobel Prize in Physics 2019
|
Externo |
Passing Juice |
|
How to Successfully Harness Machine Learning to Combat Fraud and Abuse
|
Externo |
Passing Juice |
|
Variational Inference: Foundations and Innovations
|
Externo |
Passing Juice |
|
Variational Inference: Foundations and Innovations
|
Externo |
Passing Juice |
|
Anomaly Detection using Neural Networks
|
Externo |
Passing Juice |
|
Extreme Value Theory
|
Externo |
Passing Juice |
|
Recurrent Neural Networks
|
Externo |
Passing Juice |
|
When deep learning does not learn,
|
Externo |
Passing Juice |
|
Optimality in Locally Private Estimation and Learning
|
Externo |
Passing Juice |
|
Capsule Networks
|
Externo |
Passing Juice |
|
A multi-perspective introduction to the EM algorithm
|
Externo |
Passing Juice |
|
Theoretical Perspectives on Deep Learning
|
Externo |
Passing Juice |
|
2018 ACM Turing Award
|
Externo |
Passing Juice |
|
Human in the Loop Reinforcement Learning
|
Externo |
Passing Juice |
|
How Graph Technology Is Changing Artificial Intelligence and Machine Learning
|
Externo |
Passing Juice |
|
2017 Nobel Lectures in Physics
|
Externo |
Passing Juice |
|
Accessorize to a Crime: Real and Stealthy Attacks on State-Of-The-Art Face Recognition
|
Externo |
Passing Juice |
|
paper
|
Externo |
Passing Juice |
|
Build Intelligent Fraud Prevention with ML and Graphs
|
Externo |
Passing Juice |
|
Active Learning: Why Smart Labeling is the Future of Data Annotation
|
Externo |
Passing Juice |
|
Generalization, Interpolation, and Neural Nets
|
Externo |
Passing Juice |
|
Similarity learning using deep neural networks
|
Externo |
Passing Juice |
|
First lecture of MIT course 6.S091)
|
Externo |
Passing Juice |
|
Dataset shift in machine learning
|
Externo |
Passing Juice |
|
2015 IAAA Winner Intelligent Surgical Scheduling System
|
Externo |
Passing Juice |
|
Artificial Intelligence Machine Learning Big Data, Exponential Finance
|
Externo |
Passing Juice |
|
Bayesian Deep Learning with Edward (and a trick using Dropout)
|
Externo |
Passing Juice |
|
Ouroboros
|
Externo |
Passing Juice |
|
Cosmos Proof of Stake
|
Externo |
Passing Juice |
|
Geometric Deep Learning
|
Externo |
Passing Juice |
|
Deep Generative Networks as Inverse Problems
|
Externo |
Passing Juice |
|
Convex Optimization and Applications
|
Externo |
Passing Juice |
|
Reinforcement Learning in Healthcare: Challenges and Promise –
|
Externo |
Passing Juice |
|
Fièrement propulsé par WordPress
|
Externo |
Passing Juice |