Nicolas Drougard

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All published works

Action	Title	Year	Authors
+ PDF Chat	Offline Risk-sensitive RL with Partial Observability to Enhance Performance in Human-Robot Teaming	2024	Giorgio Angelotti Caroline Ponzoni Carvalho Chanel Adam H. M. Pinto Christophe Lounis Corentin Chauffaut Nicolas Drougard
+	Data Augmentation Through Expert-Guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning	2023	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	Expert-guided Symmetry Detection in Markov Decision Processes	2022	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+ PDF Chat	Exploiting Expert-guided Symmetry Detection in Markov Decision Processes	2021	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	Exploitation vs Caution: Risk-sensitive Policies for Offline Learning.	2021	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	An Offline Risk-aware Policy Selection Method for Bayesian Markov Decision Processes	2021	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	Data Augmentation through Expert-guided Symmetry Detection to Improve Performance in Offline Reinforcement Learning	2021	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+ PDF Chat	Offline Learning for Planning: A Summary	2020	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	Offline Learning for Planning: A Summary	2020	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	Offline Learning for Planning: A Summary	2020	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel
+	One Class Splitting Criteria for Random Forests	2016	Nicolas Goix Nicolas Drougard Romain Brault Maël Chiapino
+	Qualitative Possibilistic Mixed-Observable MDPs	2013	Nicolas Drougard Florent Teichteil-Königsbuch Jean-Loup Farges Didier Dubois

Common Coauthors

Coauthor	Papers Together
Giorgio Angelotti	10
Caroline Ponzoni Carvalho Chanel	10
Maël Chiapino	1
Nicolas Goix	1
Corentin Chauffaut	1
Florent Teichteil-Königsbuch	1
Romain Brault	1
Adam H. M. Pinto	1
Didier Dubois	1
Jean-Loup Farges	1
Christophe Lounis	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems	2020	Sergey Levine Aviral Kumar George Tucker Justin Fu	3
+ PDF Chat	Normalizing Flows: An Introduction and Review of Current Methods	2020	Ivan Kobyzev Simon J. D. Prince Marcus A. Brubaker	2
+	NICE: Non-linear Independent Components Estimation	2014	Laurent Dinh David Krueger Yoshua Bengio	2
+	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction	2019	Aviral Kumar Justin Fu Matthew Soh George Tucker Sergey Levine	2
+	MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning	2020	Elise van der Pol Daniel E. Worrall Herke van Hoof Frans A. Oliehoek Max Welling	2
+	Plannable Approximations to MDP Homomorphisms: Equivariance under Actions	2020	Elise van der Pol Thomas Kipf Frans A. Oliehoek Max Welling	2
+	Benchmarking Batch Deep Reinforcement Learning Algorithms	2019	Scott Fujimoto Edoardo Conti Mohammad Ghavamzadeh Joëlle Pineau	2
+	FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models	2018	Will Grathwohl Ricky T. Q. Chen Jesse Bettencourt Ilya Sutskever David Duvenaud	2
+	OpenAI Gym	2016	Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba	2
+	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
+ PDF Chat	Robust and Adaptive Planning under Model Uncertainty	2019	Apoorva Sharma J. Michael Harrison Matthew Tsao Marco Pavone	1
+	Behavior Regularized Offline Reinforcement Learning	2019	Yifan Wu George Tucker Ofir Nachum	1
+	A possibilistic model for qualitative sequential decision problems under uncertainty in partially observable environments	1999	Régis Sabbadin	1
+	Dream to Control: Learning Behaviors by Latent Imagination	2019	Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi	1
+ PDF Chat	Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes	2020	Pablo Samuel Castro	1
+	D4RL: Datasets for Deep Data-Driven Reinforcement Learning	2020	Justin Fu Aviral Kumar Ofir Nachum George Tucker Sergey Levine	1
+ PDF Chat	How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics	2019	Anirudha Majumdar Marco Pavone	1
+	MOPO: Model-based Offline Policy Optimization	2020	Tianhe Yu Garrett Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma	1
+	Conservative Q-Learning for Offline Reinforcement Learning	2020	Aviral Kumar Aurick Zhou George Tucker Sergey Levine	1
+ PDF Chat	Analyzing and Improving the Image Quality of StyleGAN	2020	Tero Karras Samuli Laine Miika Aittala Janne Hellsten Jaakko Lehtinen Timo Aila	1
+	MOPO: Model-based Offline Policy Optimization	2020	Tianhe Yu Garrett Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma	1
+	Expert-guided Symmetry Detection in Markov Decision Processes	2022	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel	1
+	Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning	2022	Denis Yarats David Brandfonbrener Hao Liu Michael Laskin Pieter Abbeel Alessandro Lazaric Lerrel Pinto	1
+	Offline Learning for Planning: A Summary	2020	Giorgio Angelotti Nicolas Drougard Caroline Ponzoni Carvalho Chanel	1
+	Hyperparameter Selection for Offline Reinforcement Learning	2020	Tom Le Paine Cosmin Păduraru Andrea Michi Çaǧlar Gülçehre Konrad Żołna Alexander S. Novikov Ziyu Wang Nando de Freitas	1
+	Masked Autoregressive Flow for Density Estimation	2017	George Papamakarios Theo Pavlakou Iain Murray	1
+	GenDICE: Generalized Offline Estimation of Stationary Values	2020	Ruiyi Zhang Bo Dai Lihong Li Dale Schuurmans	1
+ PDF Chat	A Markovian Decision Process	1957	Richard Bellman	1
+	Consistency of random forests	2015	Erwan Scornet Gérard Biau Jean‐Philippe Vert	1
+	Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm	2017	David Silver Thomas Hubert Julian Schrittwieser Ioannis Antonoglou Matthew Lai Arthur Guez Marc Lanctot Laurent Sifre Dharshan Kumaran Thore Graepel	1
+	Model-Based Reinforcement Learning for Atari	2019	Łukasz Kaiser Mohammad Babaeizadeh Piotr Miłoś Błażej Osiński Roy H. Campbell Konrad Czechowski Dumitru Erhan Chelsea Finn Piotr Kozakowski Sergey Levine	1
+ PDF Chat	SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition	2019	Daniel Park William Chan Yu Zhang Chung‐Cheng Chiu Barret Zoph Ekin D. Cubuk Quoc V. Le	1
+	Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog	2019	Natasha Jaques Asma Ghandeharioun Judy Hanwen Shen Craig Ferguson Àgata Lapedriza Noah Jones Shixiang Gu Rosalind W. Picard	1
+ PDF Chat	Multi-agent Diverse Generative Adversarial Networks	2018	Arnab Ghosh Viveka Kulharia Vinay P. Namboodiri Philip H. S. Torr Puneet K. Dokania	1
+	Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models	2018	Kurtland Chua Roberto Calandra Rowan McAllister Sergey Levine	1