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2020 – today
- 2024
[c58]Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba:
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. ICLR 2024- [c57]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR 2024 - [c56]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, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Lin, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Ian Steneker, David Campbell, Brad Jokubaitis, Steven Basart, Stephen Fitz, Ponnurangam Kumaraguru, Kallol Krishna Karmakar, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks:
The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning. ICML 2024 - [i56]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, Rassin Lababidi, Lennart Justen
, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Adam Khoja, Zhenqi Zhao, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Liu, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Russell Kaplan, Ian Steneker, David Campbell, Brad Jokubaitis, Alex Levinson, Jean Wang, William Qian, Kallol Krishna Karmakar, Steven Basart, Stephen Fitz, Mindy Levine, Ponnurangam Kumaraguru, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks:
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. CoRR abs/2403.03218 (2024) - [i55]Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang:
Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR abs/2407.21170 (2024) - [i54]Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang:
Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. CoRR abs/2409.00844 (2024) - 2023
- [c55]Anastasia Razdaibiedina, Yuning Mao, Madian Khabsa, Mike Lewis, Rui Hou, Jimmy Ba, Amjad Almahairi:
Residual Prompt Tuning: improving prompt tuning with residual reparameterization. ACL (Findings) 2023: 6740-6757 - [c54]Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang:
Decomposed Prompting to Answer Questions on a Course Discussion Board. AIED (Posters/Late Breaking Results/...) 2023: 218-223 - [c53]Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse:
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR 2023 - [c52]Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba:
Large Language Models are Human-Level Prompt Engineers. ICLR 2023 - [c51]Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem:
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. ICML 2023: 22092-22112 - [c50]Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang:
Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) 2023: 658 - [c49]Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu:
Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective. NeurIPS 2023 - [c48]Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS 2023 - [c47]Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith:
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. NeurIPS 2023 - [i53]Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy P. Lillicrap:
Mastering Diverse Domains through World Models. CoRR abs/2301.04104 (2023) - [i52]Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba:
Boosted Prompt Ensembles for Large Language Models. CoRR abs/2304.05970 (2023) - [i51]Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem:
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. CoRR abs/2304.13742 (2023) - [i50]Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Jimmy Ba, Amjad Almahairi:
Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization. CoRR abs/2305.03937 (2023) - [i49]Augustin Toma, Patrick R. Lawler, Jimmy Ba, Rahul G. Krishnan, Barry B. Rubin, Bo Wang:
Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding. CoRR abs/2305.12031 (2023) - [i48]Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR abs/2305.14387 (2023) - [i47]Yongchao Zhou, Hshmat Sahak, Jimmy Ba:
Training on Thin Air: Improve Image Classification with Generated Data. CoRR abs/2305.15316 (2023) - [i46]Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith:
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. CoRR abs/2306.00937 (2023) - [i45]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR abs/2309.15817 (2023) - [i44]Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba:
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. CoRR abs/2310.06786 (2023) - [i43]Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba:
Using Large Language Models for Hyperparameter Optimization. CoRR abs/2312.04528 (2023) - 2022
- [c46]Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang:
Understanding the Variance Collapse of SVGD in High Dimensions. ICLR 2022 - [c45]Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang:
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. NeurIPS 2022 - [c44]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. NeurIPS 2022 - [c43]Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba:
Dataset Distillation using Neural Feature Regression. NeurIPS 2022 - [i42]Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang:
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. CoRR abs/2205.01445 (2022) - [i41]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. CoRR abs/2205.15967 (2022) - [i40]Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba:
Dataset Distillation using Neural Feature Regression. CoRR abs/2206.00719 (2022) - [i39]Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez:
Exploring Low Rank Training of Deep Neural Networks. CoRR abs/2209.13569 (2022) - [i38]Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba:
Large Language Models Are Human-Level Prompt Engineers. CoRR abs/2211.01910 (2022) - [i37]Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse:
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR abs/2212.03905 (2022) - 2021
- [c42]Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu:
When does preconditioning help or hurt generalization? ICLR 2021 - [c41]Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba:
Mastering Atari with Discrete World Models. ICLR 2021 - [c40]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
Planning from Pixels using Inverse Dynamics Models. ICLR 2021 - [c39]Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger Baker Grosse:
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. ICLR 2021 - [c38]Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba:
Efficient Statistical Tests: A Neural Tangent Kernel Approach. ICML 2021: 4893-4903 - [c37]Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy:
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. ICML 2021: 11251-11262 - [c36]Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba:
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS 2021: 764-776 - [c35]Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba:
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? NeurIPS 2021: 9788-9803 - [c34]Vaibhav Saxena, Jimmy Ba, Danijar Hafner:
Clockwork Variational Autoencoders. NeurIPS 2021: 29246-29257 - [i36]Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy:
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. CoRR abs/2101.06223 (2021) - [i35]Vaibhav Saxena, Jimmy Ba, Danijar Hafner:
Clockwork Variational Autoencoders. CoRR abs/2102.09532 (2021) - [i34]Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba:
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR abs/2110.14248 (2021) - 2020
- [c33]Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba:
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS 2020: 3621-3631 - [c32]Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang:
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint. ICLR 2020 - [c31]Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi:
Dream to Control: Learning Behaviors by Latent Imagination. ICLR 2020 - [c30]Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba:
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. ICLR 2020 - [c29]Tingwu Wang, Jimmy Ba:
Exploring Model-based Planning with Policy Networks. ICLR 2020 - [c28]Yuanhao Wang, Guodong Zhang, Jimmy Ba:
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. ICLR 2020 - [c27]Yeming Wen, Dustin Tran, Jimmy Ba:
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. ICLR 2020 - [c26]Xiao Shi Huang, Felipe Pérez, Jimmy Ba, Maksims Volkovs:
Improving Transformer Optimization Through Better Initialization. ICML 2020: 4475-4483 - [c25]Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba:
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. ICML 2020: 7750-7761 - [c24]Bradly C. Stadie, Lunjun Zhang, Jimmy Ba:
Learning Intrinsic Rewards as a Bi-Level Optimization Problem. UAI 2020: 111-120 - [i33]Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba:
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. CoRR abs/2002.05825 (2020) - [i32]Yeming Wen, Dustin Tran, Jimmy Ba:
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. CoRR abs/2002.06715 (2020) - [i31]Shun-ichi Amari, Jimmy Ba, Roger B. Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu:
When Does Preconditioning Help or Hurt Generalization? CoRR abs/2006.10732 (2020) - [i30]Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba:
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. CoRR abs/2007.02832 (2020) - [i29]Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger B. Grosse:
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. CoRR abs/2007.02924 (2020) - [i28]Yuhuai Wu, Honghua Dong, Roger B. Grosse, Jimmy Ba:
The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning. CoRR abs/2007.04212 (2020) - [i27]Fartash Faghri, David Duvenaud, David J. Fleet, Jimmy Ba:
A Study of Gradient Variance in Deep Learning. CoRR abs/2007.04532 (2020) - [i26]Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl J. Friston, Nicolas Heess:
Action and Perception as Divergence Minimization. CoRR abs/2009.01791 (2020) - [i25]Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba:
Mastering Atari with Discrete World Models. CoRR abs/2010.02193 (2020) - [i24]Keiran Paster, Sheila A. McIlraith, Jimmy Ba:
Planning from Pixels using Inverse Dynamics Models. CoRR abs/2012.02419 (2020) - [i23]Brendon Matusch, Jimmy Ba, Danijar Hafner:
Evaluating Agents without Rewards. CoRR abs/2012.11538 (2020) - [i22]Jingling Li, Mozhi Zhang, Keyulu Xu, John P. Dickerson, Jimmy Ba:
Noisy Labels Can Induce Good Representations. CoRR abs/2012.12896 (2020)
2010 – 2019
- 2019
- [c23]Sheng Jia, Jamie Kiros, Jimmy Ba:
DOM-Q-NET: Grounded RL on Structured Language. ICLR (Poster) 2019 - [c22]Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba:
Neural Graph Evolution: Towards Efficient Automatic Robot Design. ICLR (Poster) 2019 - [c21]Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton:
Lookahead Optimizer: k steps forward, 1 step back. NeurIPS 2019: 9593-9604 - [c20]Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky:
Graph Normalizing Flows. NeurIPS 2019: 13556-13566 - [i21]Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba:
ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning. CoRR abs/1902.04546 (2019) - [i20]Sheng Jia, Jamie Kiros, Jimmy Ba:
DOM-Q-NET: Grounded RL on Structured Language. CoRR abs/1902.07257 (2019) - [i19]Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba:
Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR abs/1902.08234 (2019) - [i18]Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky:
Graph Normalizing Flows. CoRR abs/1905.13177 (2019) - [i17]Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba:
Neural Graph Evolution: Towards Efficient Automatic Robot Design. CoRR abs/1906.05370 (2019) - [i16]Tingwu Wang, Jimmy Ba:
Exploring Model-based Planning with Policy Networks. CoRR abs/1906.08649 (2019) - [i15]Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba:
Benchmarking Model-Based Reinforcement Learning. CoRR abs/1907.02057 (2019) - [i14]Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba:
Lookahead Optimizer: k steps forward, 1 step back. CoRR abs/1907.08610 (2019) - [i13]Yuanhao Wang, Guodong Zhang, Jimmy Ba:
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. CoRR abs/1910.07512 (2019) - [i12]Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi:
Dream to Control: Learning Behaviors by Latent Imagination. CoRR abs/1912.01603 (2019) - 2018
- [c19]James Martens, Jimmy Ba, Matt Johnson:
Kronecker-factored Curvature Approximations for Recurrent Neural Networks. ICLR (Poster) 2018 - [c18]Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler:
NerveNet: Learning Structured Policy with Graph Neural Networks. ICLR (Poster) 2018 - [c17]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) 2018 - [c16]Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee:
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS 2018: 7091-7101 - [c15]Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse:
Reversible Recurrent Neural Networks. NeurIPS 2018: 9043-9054 - [i11]Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee:
Solving Approximate Wasserstein GANs to Stationarity. CoRR abs/1802.08249 (2018) - [i10]Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse:
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR abs/1803.04386 (2018) - [i9]Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse:
Reversible Recurrent Neural Networks. CoRR abs/1810.10999 (2018) - 2017
- [c14]Jimmy Ba, Roger B. Grosse, James Martens:
Distributed Second-Order Optimization using Kronecker-Factored Approximations. ICLR (Poster) 2017 - [c13]Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba:
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation. NIPS 2017: 5279-5288 - [i8]Yuhuai Wu, Elman Mansimov, Shun Liao, Roger B. Grosse, Jimmy Ba:
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation. CoRR abs/1708.05144 (2017) - 2016
- [j1]Oren Z. Kraus, Lei Jimmy Ba, Brendan J. Frey:
Classifying and segmenting microscopy images with deep multiple instance learning. Bioinform. 32(12): 52-59 (2016) - [c12]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. NIPS 2016: 4331-4339 - [c11]Elman Mansimov, Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov:
Generating Images from Captions with Attention. ICLR 2016 - [c10]Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov:
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning. ICLR (Poster) 2016 - [i7]Lei Jimmy Ba, Jamie Ryan Kiros, Geoffrey E. Hinton:
Layer Normalization. CoRR abs/1607.06450 (2016) - [i6]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. CoRR abs/1610.06258 (2016) - 2015
- [c9]Steve Mann, Ryan E. Janzen, Valmiki Rampersad, Jason Huang, Lei Jimmy Ba:
"SQUEAKeys": A friction idiophone, for physical interaction with mobile devices. GEM 2015: 1-4 - [c8]Lei Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov:
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions. ICCV 2015: 4247-4255 - [c7]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. ICML 2015: 2048-2057 - [c6]Jimmy Ba, Ruslan Salakhutdinov, Roger B. Grosse, Brendan J. Frey:
Learning Wake-Sleep Recurrent Attention Models. NIPS 2015: 2593-2601 - [c5]Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu:
Multiple Object Recognition with Visual Attention. ICLR (Poster) 2015 - [c4]Diederik P. Kingma, Jimmy Ba:
Adam: A Method for Stochastic Optimization. ICLR (Poster) 2015 - [i5]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR abs/1502.03044 (2015) - [i4]Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov:
Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptions. CoRR abs/1506.00511 (2015) - [i3]Jimmy Ba, Roger B. Grosse, Ruslan Salakhutdinov, Brendan J. Frey:
Learning Wake-Sleep Recurrent Attention Models. CoRR abs/1509.06812 (2015) - [i2]Oren Z. Kraus, Lei Jimmy Ba, Brendan J. Frey:
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning. CoRR abs/1511.05286 (2015) - 2014
- [c3]Jimmy Ba, Rich Caruana:
Do Deep Nets Really Need to be Deep? NIPS 2014: 2654-2662 - 2013
- [c2]Lei Jimmy Ba, Brendan J. Frey:
Adaptive dropout for training deep neural networks. NIPS 2013: 3084-3092 - [i1]Lei Jimmy Ba, Rich Caruana:
Do Deep Nets Really Need to be Deep? CoRR abs/1312.6184 (2013) - 2011
- [c1]Steve Mann, Ryan E. Janzen, Jason Huang, Matthew B. Kelly, Lei Jimmy Ba, Alexander Chen:
User-interfaces based on the water-hammer effect: water-hammer piano as an interactive percussion surface. TEI 2011: 1-8
Coauthor Index
Roger B. Grosse
aka: Roger Baker Grosse
aka: Roger Baker Grosse
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