Tamara Gerbert

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All published works

Action	Title	Year	Authors
+	Analysing deep reinforcement learning agents trained with domain randomisation	2022	Tianhong Dai Kai Arulkumaran Tamara Gerbert Samyakh Tukra Feryal Behbahani Anil A. Bharath
+	Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation	2019	Tianhong Dai Kai Arulkumaran Tamara Gerbert Samyakh Tukra Feryal Behbahani Anil A. Bharath

Common Coauthors

Coauthor	Papers Together
Feryal Behbahani	2
Anil A. Bharath	2
Kai Arulkumaran	2
Samyakh Tukra	2
Tianhong Dai	1
Tianhong Dai	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification	2015	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	On the difficulty of training Recurrent Neural Networks	2012	Razvan Pascanu Tomáš Mikolov Yoshua Bengio	1
+ PDF Chat	Understanding deep image representations by inverting them	2015	Aravindh Mahendran Andrea Vedaldi	1
+ PDF Chat	Deep neural networks are easily fooled: High confidence predictions for unrecognizable images	2015	Anh‐Tu Nguyen Jason Yosinski Jeff Clune	1
+ PDF Chat	Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation	2014	Ross Girshick Jeff Donahue Trevor Darrell Jitendra Malik	1
+	End-to-End Training of Deep Visuomotor Policies	2015	Sergey Levine Chelsea Finn Trevor Darrell Pieter Abbeel	1
+ PDF Chat	LIII. <i>On lines and planes of closest fit to systems of points in space</i>	1901	Karl Pearson	1
+ PDF Chat	Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates	2017	Shixiang Gu Ethan Holly Timothy Lillicrap Sergey Levine	1
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	1
+	Learning Important Features Through Propagating Activation Differences	2017	Avanti Shrikumar Peyton Greenside Anshul Kundaje	1
+	An Entropy-based Pruning Method for CNN Compression	2017	Jian-Hao Luo Jianxin Wu	1
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	1
+	UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction	2018	Leland McInnes John J. Healy	1
+	Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research	2018	Matthias Plappert Marcin Andrychowicz Alex Ray Bob McGrew Bowen Baker Glenn Powell Jonas Schneider Josh Tobin Maciek Chociej Peter Welinder	1
+	A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning	2018	Amy Zhang Nicolas Ballas Joëlle Pineau	1
+	Procedural Level Generation Improves Generality of Deep Reinforcement Learning	2018	Niels Justesen Rubén Rodríguez Torrado Philip Bontrager Ahmed Khalifa Julian Togelius Sebastian Risi	1
+	Learning Dexterous In-Hand Manipulation	2018	OpenAI	1
+	Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience	2018	Yevgen Chebotar Ankur Handa Viktor Makoviychuk Miles Macklin Jan Issac Nathan Ratliff Dieter Fox	1
+	Assessing Generalization in Deep Reinforcement Learning	2018	Charles Packer Katelyn Gao Jernej Kos Philipp Krähenbühl Vladlen Koltun Dawn Song	1
+	Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms	2018	Andrew Ilyas Logan Engstrom Shibani Santurkar Dimitris Tsipras Firdaus Janoos Larry Rudolph Aleksander Mądry	1
+	Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures.	2018	Jonathan Uesato Ananya Kumar Csaba Szepesvári Tom Erez Avraham Ruderman Keith Anderson Krishmamurthy Dvijotham Nicolas Heess Pushmeet Kohli	1
+	Quantifying Generalization in Reinforcement Learning	2018	Karl Cobbe Oleg Klimov Chris Hesse Taehoon Kim John Schulman	1
+	Are All Layers Created Equal?	2019	Chiyuan Zhang Samy Bengio Yoram Singer	1
+	Investigating Generalisation in Continuous Deep Reinforcement Learning	2019	Chenyang Zhao Olivier Sigaud Freek Stulp Timothy M. Hospedales	1
+ PDF Chat	A Survey of Methods for Explaining Black Box Models	2018	Riccardo Guidotti Anna Monreale Salvatore Ruggieri Franco Turini Fosca Giannotti Dino Pedreschi	1
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	1
+ PDF Chat	Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping	2018	Konstantinos Bousmalis Alex Irpan Paul Wohlhart Yunfei Bai Matthew Kelcey Mrinal Kalakrishnan Laura Downs Julian Ibarz Peter Pástor Kurt Konolige	1
+	Pruning Filters for Efficient ConvNets	2016	Hao Li Asim Kadav Igor Đurđanović Hanan Samet Hans Peter Graf	1
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	1
+	Towards Deep Learning Models Resistant to Adversarial Attacks.	2018	Aleksander Mądry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu	1
+	Emergent Systematic Generalization in a Situated Agent	2019	Felix Hill Andrew K. Lampinen Rosalia Schneider Stephen Clark Matthew Botvinick James L. McClelland Adam Santoro	1
+ PDF Chat	Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI	2019	Alejandro Barredo Arrieta Natalia Díaz-Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik Alberto Barbado Salvador García Sergio Gil-López Daniel Molina Richard Benjamins	1
+ PDF Chat	Learning dexterous in-hand manipulation	2019	OpenAI Marcin Andrychowicz Bowen Baker Maciek Chociej Rafał Józefowicz Bob McGrew Jakub Pachocki Arthur J Petron Matthias Plappert Glenn Powell Alex Ray	1
+	Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations	2020	Pedro Sequeira Melinda Gervasio	1
+ PDF Chat	DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning	2020	Théo Jaunet Romain Vuillemot Christian Wolf	1
+ PDF Chat	Deep Reinforcement Learning: A Brief Survey	2017	Kai Arulkumaran Marc Peter Deisenroth Miles Brundage Anil A. Bharath	1
+ PDF Chat	Sim-to-Real Transfer of Robotic Control with Dynamics Randomization	2018	Xue Bin Peng Marcin Andrychowicz Wojciech Zaremba Pieter Abbeel	1
+ PDF Chat	An Introduction to Deep Reinforcement Learning	2018	Vincent François-Lavet Peter Henderson Riashat Islam Marc G. Bellemare Joëlle Pineau	1
+	Counterfactual state explanations for reinforcement learning agents via generative deep learning	2021	Matthew Olson Roli Khanna Lawrence Neal Fuxin Li Weng‐Keen Wong	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James T. Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+	Quantifying Generalization in Reinforcement Learning	2018	Karl Cobbe О. В. Климов Chris Hesse Taehoon Kim John Schulman	1
+	Hindsight Experience Replay	2017	Marcin Andrychowicz Filip Wolski Alex Ray Jonas Schneider Rachel H. Fong Peter Welinder Bob McGrew Joshua W.D. Tobin Pieter Abbeel Wojciech Zaremba	1