Jimmy Ba

48 papers · 2013–2024 · 6 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (11) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6)

🌍 Conference Polyglot (6) 🏃 Academic Marathon (11) 🌈 Renaissance Researcher (7) 🏠 Conference Loyalist (20) 🌱 Topic Pioneer 👥 Mega-Team (46) 👑 Triple Crown 🧬 Topic Evolution 🗃️ Keyword Collector (140) ⚡ Prolific Year (5) 🚀 Conference Pioneer 💎 Century Club (48) 🔥 Unstoppable (12) 📈 Trend Setter ❓ The Questioner (3)

Conferences

ICLR (20) NIPS (18) ICML (7) ACL (1) AISTATS (1) UAI (1)

Top co-authors

Keiran Paster (6) Harris Chan (6) Denny Wu (5) Taiji Suzuki (5) Silviu Pitis (4) Roger B Grosse (4) Yuhuai Wu (4) Murat A Erdogdu (3) Yongchao Zhou (3) Tingwu Wang (3)

Research topics

Reinforcement Learning (1)

Keywords

neural network (5) representation learning (4) gradient descent (3) generative model (3) stochastic gradient descent (3) reinforcement learning (3) deep neural network (2) instruction following (2) image captioning (2) kernel methods (2) image classification (1) sample efficiency (1) feature learning (1) neural network training (1) zero-shot learning (1) model compression (1) transfer learning (1) continual learning (1) stochastic gradient (1) domain generalization (1)

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 STEVE-1: A Generative Model for Text-to-Behavior in Minecraft NIPS 2023 Residual Prompt Tuning: improving prompt tuning with residual reparameterization ACL 2023 TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation ICML 2023 Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective NIPS 2023 Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve ICLR 2023 Large Language Models are Human-Level Prompt Engineers ICLR 2023 AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback NIPS 2023 High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation NIPS 2022 Understanding the Variance Collapse of SVGD in High Dimensions ICLR 2022 Dataset Distillation using Neural Feature Regression NIPS 2022 You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments NIPS 2022 Mastering Atari with Discrete World Models ICLR 2021 Planning from Pixels using Inverse Dynamics Models ICLR 2021 LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning ICML 2021 Efficient Statistical Tests: A Neural Tangent Kernel Approach ICML 2021 Learning Domain Invariant Representations in Goal-conditioned Block MDPs NIPS 2021 How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? NIPS 2021 Clockwork Variational Autoencoders NIPS 2021 When does preconditioning help or hurt generalization? ICLR 2021 INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving ICLR 2021 Learning Intrinsic Rewards as a Bi-Level Optimization Problem UAI 2020 An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020 Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint ICLR 2020 On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach ICLR 2020 BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning ICLR 2020 Dream to Control: Learning Behaviors by Latent Imagination ICLR 2020 An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality ICLR 2020 Exploring Model-based Planning with Policy Networks ICLR 2020 Improving Transformer Optimization Through Better Initialization ICML 2020 Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning ICML 2020 Lookahead Optimizer: k steps forward, 1 step back NIPS 2019 Graph Normalizing Flows NIPS 2019 Neural Graph Evolution: Towards Efficient Automatic Robot Design ICLR 2019 DOM-Q-NET: Grounded RL on Structured Language ICLR 2019 Reversible Recurrent Neural Networks NIPS 2018 Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches ICLR 2018 NerveNet: Learning Structured Policy with Graph Neural Networks ICLR 2018 Kronecker-factored Curvature Approximations for Recurrent Neural Networks ICLR 2018 On the Convergence and Robustness of Training GANs with Regularized Optimal Transport NIPS 2018 Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS 2017 Using Fast Weights to Attend to the Recent Past NIPS 2016 Learning Wake-Sleep Recurrent Attention Models NIPS 2015 Show, Attend and Tell: Neural Image Caption Generation with Visual Attention ICML 2015 Do Deep Nets Really Need to be Deep? NIPS 2014 Adaptive dropout for training deep neural networks NIPS 2013