Jimmy Ba
48 papers · 2013–2024 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (93) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Research topics
Machine Learning
(33)
Deep Learning
(28)
Artificial Intelligence
(22)
Core AI
(20)
Architectures
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Optimization & Theory Β· Machine Learning
(15)
Learning Types Β· Machine Learning
(11)
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Reinforcement Learning
(8)
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Optimization & Theory Β· Deep Learning
(7)
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(7)
Natural Language Processing
(6)
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neural network
(8)
reinforcement learning
(6)
graph neural network
(5)
representation learning
(4)
gradient descent
(4)
large language model
(4)
sample efficiency
(3)
zero-shot learning
(3)
stochastic gradient descent
(3)
generative model
(3)
model-based reinforcement learning
(3)
latent space
(3)
continuous control
(3)
model compression
(2)
deep neural network
(2)
variational autoencoder
(2)
maximum mean discrepancy
(2)
few-shot learning
(2)
instruction following
(2)
mathematical reasoning
(2)
Papers
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
ICLR 2024
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text
ICLR 2024
The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning
ICML 2024
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
NeurIPS 2023
Large Language Models are Human-Level Prompt Engineers
ICLR 2023
Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective
NeurIPS 2023
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
ICLR 2023
Residual Prompt Tuning: improving prompt tuning with residual reparameterization
ACL 2023
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
NeurIPS 2023
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation
ICML 2023
Dataset Distillation using Neural Feature Regression
NeurIPS 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
NeurIPS 2022
Understanding the Variance Collapse of SVGD in High Dimensions
ICLR 2022
You Canβt Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments
NeurIPS 2022
Clockwork Variational Autoencoders
NeurIPS 2021
Efficient Statistical Tests: A Neural Tangent Kernel Approach
ICML 2021
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels?
NeurIPS 2021
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving
ICLR 2021
Learning Domain Invariant Representations in Goal-conditioned Block MDPs
NeurIPS 2021
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
ICML 2021
Mastering Atari with Discrete World Models
ICLR 2021
Planning from Pixels using Inverse Dynamics Models
ICLR 2021
When does preconditioning help or hurt generalization?
ICLR 2021
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise
AISTATS 2020
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality
ICLR 2020
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
ICLR 2020
Dream to Control: Learning Behaviors by Latent Imagination
ICLR 2020
Exploring Model-based Planning with Policy Networks
ICLR 2020
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint
ICLR 2020
Improving Transformer Optimization Through Better Initialization
ICML 2020
Learning Intrinsic Rewards as a Bi-Level Optimization Problem
UAI 2020
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
ICML 2020
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
ICLR 2020
DOM-Q-NET: Grounded RL on Structured Language
ICLR 2019
Graph Normalizing Flows
NeurIPS 2019
Lookahead Optimizer: k steps forward, 1 step back
NeurIPS 2019
Neural Graph Evolution: Towards Efficient Automatic Robot Design
ICLR 2019
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
ICLR 2018
Kronecker-factored Curvature Approximations for Recurrent Neural Networks
ICLR 2018
NerveNet: Learning Structured Policy with Graph Neural Networks
ICLR 2018
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
NeurIPS 2018
Reversible Recurrent Neural Networks
NeurIPS 2018
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
NeurIPS 2017
Using Fast Weights to Attend to the Recent Past
NeurIPS 2016
Learning Wake-Sleep Recurrent Attention Models
NeurIPS 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
ICML 2015
Do Deep Nets Really Need to be Deep?
NeurIPS 2014
Adaptive dropout for training deep neural networks
NeurIPS 2013