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ORCIDTimothy A. Mann
Person information
- affiliation: Google DeepMind, London, UK
Other persons with a similar name
- Timothy Mann — disambiguation page
- Timothy P. Mann — VMWare Inc., Palo Alto, CA, USA (and 1 more)
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2020 – today
- 2022
[c29]Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal:
Defending Against Image Corruptions Through Adversarial Augmentations. ICLR 2022- [i27]Amol Mandhane, Anton Zhernov, Maribeth Rauh, Chenjie Gu, Miaosen Wang, Flora Xue, Wendy Shang, Derek Pang, Rene Claus, Ching-Han Chiang, Cheng Chen, Jingning Han, Angie Chen, Daniel J. Mankowitz, Jackson Broshear, Julian Schrittwieser, Thomas Hubert, Oriol Vinyals, Timothy A. Mann:
MuZero with Self-competition for Rate Control in VP9 Video Compression. CoRR abs/2202.06626 (2022) - 2021
- [c28]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR 2021 - [c27]Sven Gowal, Po-Sen Huang, Aäron van den Oord, Timothy A. Mann, Pushmeet Kohli:
Self-supervised Adversarial Robustness for the Low-label, High-data Regime. ICLR 2021 - [c26]Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann:
Improving Robustness using Generated Data. NeurIPS 2021: 4218-4233 - [c25]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Data Augmentation Can Improve Robustness. NeurIPS 2021: 29935-29948 - [i26]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Fixing Data Augmentation to Improve Adversarial Robustness. CoRR abs/2103.01946 (2021) - [i25]Dan A. Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal:
Defending Against Image Corruptions Through Adversarial Augmentations. CoRR abs/2104.01086 (2021) - [i24]Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann:
Improving Robustness using Generated Data. CoRR abs/2110.09468 (2021) - [i23]Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann:
Data Augmentation Can Improve Robustness. CoRR abs/2111.05328 (2021) - 2020
- [c24]Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli:
Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations. CVPR 2020: 1208-1217 - [c23]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR 2020 - [c22]Claire Vernade, András György, Timothy A. Mann:
Non-Stationary Delayed Bandits with Intermediate Observations. ICML 2020: 9722-9732 - [c21]Anton Zhernov, Krishnamurthy (Dj) Dvijotham, Ivan Lobov, Dan A. Calian, Michelle X. Gong, Natarajan Chandrashekar, Timothy A. Mann:
The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver. KDD 2020: 1285-1294 - [i22]Claire Vernade, András György, Timothy A. Mann:
Non-Stationary Bandits with Intermediate Observations. CoRR abs/2006.02119 (2020) - [i21]Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy A. Mann, Pushmeet Kohli:
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples. CoRR abs/2010.03593 (2020) - [i20]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR abs/2010.06324 (2020) - [i19]Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin A. Riedmiller, Timothy A. Mann:
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/2010.10644 (2020)
2010 – 2019
- 2019
- [c20]Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Arthur Mann, Pushmeet Kohli:
Scalable Verified Training for Provably Robust Image Classification. ICCV 2019: 4841-4850 - [c19]Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy A. Mann, Danilo J. Rezende:
Beyond Greedy Ranking: Slate Optimization via List-CVAE. ICLR (Poster) 2019 - [c18]Timothy A. Mann, Sven Gowal, András György, Huiyi Hu, Ray Jiang, Balaji Lakshminarayanan, Prav Srinivasan:
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems. ICML 2019: 4324-4332 - [c17]Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Verify and Train Deep Networks. IJCAI 2019: 6156-6160 - [c16]Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu:
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. NeurIPS 2019: 11872-11882 - [c15]Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
A Bayesian Approach to Robust Reinforcement Learning. UAI 2019: 648-658 - [i18]Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
A Bayesian Approach to Robust Reinforcement Learning. CoRR abs/1905.08188 (2019) - [i17]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/1906.07516 (2019) - [i16]Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy A. Mann, André Barreto, Sylvain Gelly, Gergely Neu:
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. CoRR abs/1906.07987 (2019) - [i15]Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy A. Mann, Pushmeet Kohli:
An Alternative Surrogate Loss for PGD-based Adversarial Testing. CoRR abs/1910.09338 (2019) - [i14]Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli:
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations. CoRR abs/1912.03192 (2019) - 2018
- [c14]Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor:
Learning Robust Options. AAAI 2018: 6409-6416 - [c13]Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Soft-Robust Actor-Critic Policy-Gradient. UAI 2018: 208-218 - [c12]Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Scalable Verification of Deep Networks. UAI 2018: 550-559 - [i13]Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor:
Learning Robust Options. CoRR abs/1802.03236 (2018) - [i12]Ray Jiang, Sven Gowal, Timothy A. Mann, Danilo J. Rezende:
Optimizing Slate Recommendations via Slate-CVAE. CoRR abs/1803.01682 (2018) - [i11]Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Soft-Robust Actor-Critic Policy-Gradient. CoRR abs/1803.04848 (2018) - [i10]Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli:
A Dual Approach to Scalable Verification of Deep Networks. CoRR abs/1803.06567 (2018) - [i9]Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto:
Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem. CoRR abs/1807.03064 (2018) - [i8]Timothy A. Mann, Sven Gowal, Ray Jiang, Huiyi Hu, Balaji Lakshminarayanan, András György:
Learning from Delayed Outcomes with Intermediate Observations. CoRR abs/1807.09387 (2018) - [i7]Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy A. Mann, Pushmeet Kohli:
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models. CoRR abs/1810.12715 (2018) - 2017
- [c11]Timothy A. Mann, Shie Mannor, Doina Precup:
Approximate Value Iteration with Temporally Extended Actions (Extended Abstract). IJCAI 2017: 5035-5039 - 2016
- [c10]Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Adaptive Skills Adaptive Partitions (ASAP). NIPS 2016: 1588-1596 - [i6]Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Iterative Hierarchical Optimization for Misspecified Problems (IHOMP). CoRR abs/1602.03348 (2016) - [i5]Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Adaptive Skills, Adaptive Partitions (ASAP). CoRR abs/1602.03351 (2016) - [i4]Timothy A. Mann, Hugo Penedones, Shie Mannor, Todd Hester:
Adaptive Lambda Least-Squares Temporal Difference Learning. CoRR abs/1612.09465 (2016) - 2015
- [j2]Timothy A. Mann, Shie Mannor
, Doina Precup:
Approximate Value Iteration with Temporally Extended Actions. J. Artif. Intell. Res. 53: 375-438 (2015) - [c9]Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor:
Learning When to Switch between Skills in a High Dimensional Domain. AAAI Workshop: Learning for General Competency in Video Games 2015 - [c8]Assaf Hallak, François Schnitzler, Timothy A. Mann, Shie Mannor:
Off-policy Model-based Learning under Unknown Factored Dynamics. ICML 2015: 711-719 - [i3]Assaf Hallak, François Schnitzler, Timothy A. Mann, Shie Mannor:
Off-policy evaluation for MDPs with unknown structure. CoRR abs/1502.03255 (2015) - [i2]Nir Levine, Timothy A. Mann, Shie Mannor:
Actively Learning to Attract Followers on Twitter. CoRR abs/1504.04114 (2015) - [i1]Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor:
Bootstrapping Skills. CoRR abs/1506.03624 (2015) - 2014
- [c7]Timothy A. Mann, Shie Mannor:
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations. ICML 2014: 127-135 - [c6]Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor:
Time-Regularized Interrupting Options (TRIO). ICML 2014: 1350-1358 - [c5]Odalric-Ambrym Maillard, Timothy A. Mann, Shie Mannor:
How hard is my MDP?" The distribution-norm to the rescue". NIPS 2014: 1835-1843 - 2013
- [j1]Timothy A. Mann, Yunjung Park, Sungmoon Jeong, Minho Lee, Yoonsuck Choe:
Autonomous and Interactive Improvement of Binocular Visual Depth Estimation through Sensorimotor Interaction. IEEE Trans. Auton. Ment. Dev. 5(1): 74-84 (2013) - 2012
- [c4]Timothy A. Mann, Yoonsuck Choe:
Directed Exploration in Reinforcement Learning with Transferred Knowledge. EWRL 2012: 59-76 - 2011
- [c3]Timothy A. Mann, Yoonsuck Choe:
Scaling Up Reinforcement Learning through Targeted Exploration. AAAI 2011: 435-440 - 2010
- [c2]Timothy A. Mann, Yoonsuck Choe:
Prenatal to postnatal transfer of motor skills through motor-compatible sensory representations. ICDL 2010: 185-190
2000 – 2009
- 2008
- [c1]Bum Soon Jang, Timothy A. Mann, Yoonsuck Choe:
Effects of Varying the Delay Distribution in Random, Scale-free, and Small-world Networks. GrC 2008: 316-321
Coauthor Index
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