User-interfaces based on the water-hammer effect: water-hammer piano as an interactive percussion surface. - Steve Mann 001; Ryan E. Janzen; Jason Huang; Matthew B. Kelly; Lei Jimmy Ba; Alexander Chen (TEI, 2011)

Adaptive dropout for training deep neural networks. - Lei Jimmy Ba; Brendan J. Frey (NIPS, 2013)

Do Deep Nets Really Need to be Deep? - Jimmy Ba; Rich Caruana (NIPS, 2014)

"SQUEAKeys": A friction idiophone, for physical interaction with mobile devices. - Steve Mann 001; Ryan E. Janzen; Valmiki Rampersad; Jason Huang; Lei Jimmy Ba (GEM, 2015)

Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions. - Lei Jimmy Ba; Kevin Swersky; Sanja Fidler; Ruslan Salakhutdinov (ICCV, 2015)

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. - Kelvin Xu; Jimmy Ba; Ryan Kiros; Kyunghyun Cho; Aaron C. Courville; Ruslan Salakhutdinov; Richard S. Zemel; Yoshua Bengio (ICML, 2015)

Learning Wake-Sleep Recurrent Attention Models. - Jimmy Ba; Ruslan Salakhutdinov; Roger B. Grosse; Brendan J. Frey (NIPS, 2015)

Multiple Object Recognition with Visual Attention. - Jimmy Ba; Volodymyr Mnih; Koray Kavukcuoglu (ICLR (Poster), 2015)

Adam: A Method for Stochastic Optimization. - Diederik P. Kingma; Jimmy Ba (ICLR (Poster), 2015)

Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning. - Oren Z. Kraus; Lei Jimmy Ba; Brendan J. Frey (CoRR, 2015)

Using Fast Weights to Attend to the Recent Past. - Jimmy Ba; Geoffrey E. Hinton; Volodymyr Mnih; Joel Z. Leibo; Catalin Ionescu (NIPS, 2016)

Classifying and segmenting microscopy images with deep multiple instance learning. - Oren Z. Kraus; Lei Jimmy Ba; Brendan J. Frey (Bioinform., 2016)

Layer Normalization. - Lei Jimmy Ba; Jamie Ryan Kiros; Geoffrey E. Hinton (CoRR, 2016)

Generating Images from Captions with Attention. - Elman Mansimov; Emilio Parisotto; Lei Jimmy Ba; Ruslan Salakhutdinov (ICLR, 2016)

Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning. - Emilio Parisotto; Lei Jimmy Ba; Ruslan Salakhutdinov (ICLR (Poster), 2016)

Distributed Second-Order Optimization using Kronecker-Factored Approximations. - Jimmy Ba; Roger B. Grosse; James Martens (ICLR (Poster), 2017)

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation - Yuhuai Wu; Elman Mansimov; Roger B. Grosse; Shun Liao; Jimmy Ba (NIPS, 2017)

Kronecker-factored Curvature Approximations for Recurrent Neural Networks. - James Martens; Jimmy Ba; Matt Johnson (ICLR (Poster), 2018)

NerveNet: Learning Structured Policy with Graph Neural Networks. - Tingwu Wang; Renjie Liao; Jimmy Ba; Sanja Fidler (ICLR (Poster), 2018)

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. - Yeming Wen; Paul Vicol; Jimmy Ba; Dustin Tran; Roger B. Grosse (ICLR (Poster), 2018)

Reversible Recurrent Neural Networks. - Matthew MacKay; Paul Vicol; Jimmy Ba; Roger B. Grosse (NeurIPS, 2018)

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. - Maziar Sanjabi; Jimmy Ba; Meisam Razaviyayn; Jason D. Lee (NeurIPS, 2018)

Solving Approximate Wasserstein GANs to Stationarity. - Maziar Sanjabi; Jimmy Ba; Meisam Razaviyayn; Jason D. Lee (CoRR, 2018)

DOM-Q-NET: Grounded RL on Structured Language. - Sheng Jia; Jamie Kiros; Jimmy Ba (ICLR (Poster), 2019)

Neural Graph Evolution: Towards Efficient Automatic Robot Design. - Tingwu Wang; Yuhao Zhou; Sanja Fidler; Jimmy Ba (ICLR (Poster), 2019)

Graph Normalizing Flows. - Jenny Liu; Aviral Kumar; Jimmy Ba; Jamie Kiros; Kevin Swersky (NeurIPS, 2019)

Lookahead Optimizer: k steps forward, 1 step back. - Michael R. Zhang; James Lucas; Jimmy Ba; Geoffrey E. Hinton (NeurIPS, 2019)

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning. - Harris Chan; Yuhuai Wu; Jamie Kiros; Sanja Fidler; Jimmy Ba (CoRR, 2019)

Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. - Yeming Wen; Kevin Luk; Maxime Gazeau; Guodong Zhang 006; Harris Chan; Jimmy Ba (CoRR, 2019)

Benchmarking Model-Based Reinforcement Learning. - Tingwu Wang; Xuchan Bao; Ignasi Clavera; Jerrick Hoang; Yeming Wen; Eric D. Langlois 002; Shunshi Zhang 001; Guodong Zhang 006; Pieter Abbeel; Jimmy Ba (CoRR, 2019)

An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. - Yeming Wen; Kevin Luk; Maxime Gazeau; Guodong Zhang 006; Harris Chan; Jimmy Ba (AISTATS, 2020)

Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint. - Jimmy Ba; Murat A. Erdogdu; Taiji Suzuki; Denny Wu; Tianzong Zhang (ICLR, 2020)

Dream to Control: Learning Behaviors by Latent Imagination. - Danijar Hafner; Timothy P. Lillicrap; Jimmy Ba; Mohammad Norouzi 002 (ICLR, 2020)

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. - Silviu Pitis; Harris Chan; Kiarash Jamali; Jimmy Ba (ICLR, 2020)

Exploring Model-based Planning with Policy Networks. - Tingwu Wang; Jimmy Ba (ICLR, 2020)

On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. - Yuanhao Wang 001; Guodong Zhang 006; Jimmy Ba (ICLR, 2020)

BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. - Yeming Wen; Dustin Tran; Jimmy Ba (ICLR, 2020)

Improving Transformer Optimization Through Better Initialization. - Xiao Shi Huang; Felipe Pérez; Jimmy Ba; Maksims Volkovs (ICML, 2020)

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. - Silviu Pitis; Harris Chan; Stephen Zhao; Bradly C. Stadie; Jimmy Ba (ICML, 2020)

Learning Intrinsic Rewards as a Bi-Level Optimization Problem. - Bradly C. Stadie; Lunjun Zhang; Jimmy Ba (UAI, 2020)

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning. - Yuhuai Wu; Honghua Dong; Roger B. Grosse; Jimmy Ba (CoRR, 2020)

A Study of Gradient Variance in Deep Learning. - Fartash Faghri; David Duvenaud; David J. Fleet; Jimmy Ba (CoRR, 2020)

Action and Perception as Divergence Minimization. - Danijar Hafner; Pedro A. Ortega; Jimmy Ba; Thomas Parr; Karl J. Friston; Nicolas Heess (CoRR, 2020)

Evaluating Agents without Rewards. - Brendon Matusch; Jimmy Ba; Danijar Hafner (CoRR, 2020)

Noisy Labels Can Induce Good Representations. - Jingling Li; Mozhi Zhang; Keyulu Xu; John P. Dickerson; Jimmy Ba (CoRR, 2020)

When does preconditioning help or hurt generalization? - Shun-ichi Amari; Jimmy Ba; Roger Baker Grosse; Xuechen Li 005; Atsushi Nitanda; Taiji Suzuki; Denny Wu; Ji Xu (ICLR, 2021)

Mastering Atari with Discrete World Models. - Danijar Hafner; Timothy P. Lillicrap; Mohammad Norouzi 002; Jimmy Ba (ICLR, 2021)

Planning from Pixels using Inverse Dynamics Models. - Keiran Paster; Sheila A. McIlraith; Jimmy Ba (ICLR, 2021)

INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. - Yuhuai Wu; Albert Q. Jiang; Jimmy Ba; Roger Baker Grosse (ICLR, 2021)

Efficient Statistical Tests: A Neural Tangent Kernel Approach. - Sheng Jia; Ehsan Nezhadarya; Yuhuai Wu; Jimmy Ba (ICML, 2021)

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. - Yuhuai Wu; Markus N. Rabe; Wenda Li; Jimmy Ba; Roger B. Grosse; Christian Szegedy (ICML, 2021)

Learning Domain Invariant Representations in Goal-conditioned Block MDPs. - Beining Han; Chongyi Zheng; Harris Chan; Keiran Paster; Michael R. Zhang; Jimmy Ba (NeurIPS, 2021)

How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? - Jingling Li; Mozhi Zhang; Keyulu Xu; John Dickerson 001; Jimmy Ba (NeurIPS, 2021)

Clockwork Variational Autoencoders. - Vaibhav Saxena; Jimmy Ba; Danijar Hafner (NeurIPS, 2021)

Understanding the Variance Collapse of SVGD in High Dimensions. - Jimmy Ba; Murat A. Erdogdu; Marzyeh Ghassemi; Shengyang Sun; Taiji Suzuki; Denny Wu; Tianzong Zhang (ICLR, 2022)

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. - Jimmy Ba; Murat A. Erdogdu; Taiji Suzuki; Zhichao Wang; Denny Wu; Greg Yang (NeurIPS, 2022)

You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. - Keiran Paster; Sheila A. McIlraith; Jimmy Ba (NeurIPS, 2022)

Dataset Distillation using Neural Feature Regression. - Yongchao Zhou; Ehsan Nezhadarya; Jimmy Ba (NeurIPS, 2022)

You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. - Keiran Paster; Sheila A. McIlraith; Jimmy Ba (CoRR, 2022)

Exploring Low Rank Training of Deep Neural Networks. - Siddhartha Rao Kamalakara; Acyr Locatelli; Bharat Venkitesh; Jimmy Ba; Yarin Gal; Aidan N. Gomez (CoRR, 2022)

Residual Prompt Tuning: improving prompt tuning with residual reparameterization. - Anastasia Razdaibiedina; Yuning Mao; Madian Khabsa; Mike Lewis; Rui Hou; Jimmy Ba; Amjad Almahairi (ACL (Findings), 2023)

Decomposed Prompting to Answer Questions on a Course Discussion Board. - Brandon Jaipersaud; Paul Zhang; Jimmy Ba; Andrew Petersen 001; Lisa Zhang; Michael R. Zhang (AIED (Posters/Late Breaking Results/...), 2023)

Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. - Juhan Bae; Michael R. Zhang; Michael Ruan; Eric Wang; So Hasegawa; Jimmy Ba; Roger Baker Grosse (ICLR, 2023)

Large Language Models are Human-Level Prompt Engineers. - Yongchao Zhou; Andrei Ioan Muresanu; Ziwen Han; Keiran Paster; Silviu Pitis; Harris Chan; Jimmy Ba (ICLR, 2023)

TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. - Zhaoyan Liu; Noël Vouitsis; Satya Krishna Gorti; Jimmy Ba; Gabriel Loaiza-Ganem (ICML, 2023)

Classifying Course Discussion Board Questions using LLMs. - Paul Zhang; Brandon Jaipersaud; Jimmy Ba; Andrew Petersen 001; Lisa Zhang; Michael R. Zhang (ITiCSE (2), 2023)

Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective. - Jimmy Ba; Murat A. Erdogdu; Taiji Suzuki; Zhichao Wang; Denny Wu (NeurIPS, 2023)

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. - Yann Dubois; Chen Xuechen Li; Rohan Taori; Tianyi Zhang; Ishaan Gulrajani; Jimmy Ba; Carlos Guestrin; Percy Liang; Tatsunori B. Hashimoto (NeurIPS, 2023)

STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. - Shalev Lifshitz; Keiran Paster; Harris Chan; Jimmy Ba; Sheila A. McIlraith (NeurIPS, 2023)

Mastering Diverse Domains through World Models. - Danijar Hafner; Jurgis Pasukonis; Jimmy Ba; Timothy P. Lillicrap (CoRR, 2023)

Boosted Prompt Ensembles for Large Language Models. - Silviu Pitis; Michael R. Zhang; Andrew Wang; Jimmy Ba (CoRR, 2023)

Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding. - Augustin Toma; Patrick R. Lawler; Jimmy Ba; Rahul G. Krishnan; Barry B. Rubin; Bo Wang (CoRR, 2023)

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. - Yann Dubois; Xuechen Li 005; Rohan Taori; Tianyi Zhang; Ishaan Gulrajani; Jimmy Ba; Carlos Guestrin; Percy Liang; Tatsunori B. Hashimoto (CoRR, 2023)

Training on Thin Air: Improve Image Classification with Generated Data. - Yongchao Zhou; Hshmat Sahak; Jimmy Ba (CoRR, 2023)

Using Large Language Models for Hyperparameter Optimization. - Michael R. Zhang; Nishkrit Desai; Juhan Bae; Jonathan Lorraine; Jimmy Ba (CoRR, 2023)

OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. - Keiran Paster; Marco Dos Santos; Zhangir Azerbayev; Jimmy Ba (ICLR, 2024)

Identifying the Risks of LM Agents with an LM-Emulated Sandbox. - Yangjun Ruan; Honghua Dong; Andrew Wang; Silviu Pitis; Yongchao Zhou; Jimmy Ba; Yann Dubois; Chris J. Maddison; Tatsunori Hashimoto (ICLR, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Gabriel Mukobi; Nathan Helm-Burger; Rassin Lababidi; et al. (ICML, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Long Phan; Gabriel Mukobi; Nathan Helm-Burger; et al. (CoRR, 2024)

Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. - Blair Yang; Fuyang Cui; Keiran Paster; Jimmy Ba; Pashootan Vaezipoor; Silviu Pitis; Michael R. Zhang (CoRR, 2024)

Mastering diverse control tasks through world models. - Danijar Hafner; Jurgis Pasukonis; Jimmy Ba; Timothy P. Lillicrap (Nat., 2025)