Markus Hofmarcher

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All published works

Action	Title	Year	Authors
+ PDF Chat	Retrieval-Augmented Decision Transformer: External Memory for In-context RL	2024	Thomas Schmied Fabian Paischer Vihang Patil Markus Hofmarcher Razvan Pascanu Sepp Hochreiter
+ PDF Chat	Contrastive Abstraction for Reinforcement Learning	2024	Vihang Patil Markus Hofmarcher Elisabeth Rumetshofer Sepp Hochreiter
+ PDF Chat	Large Language Models Can Self-Improve At Web Agent Tasks	2024	Ajay Patel Markus Hofmarcher Claudiu Leoveanu-Condrei Marius-Constantin Dinu Chris Callison-Burch Sepp Hochreiter
+	Semantic HELM: A Human-Readable Memory for Reinforcement Learning	2023	Fabian Paischer Thomas Adler Markus Hofmarcher Sepp Hochreiter
+	Learning to Modulate pre-trained Models in RL	2023	Thomas Schmied Markus Hofmarcher Fabian Paischer Razvan Pascanu Sepp Hochreiter
+	SITTA: A Semantic Image-Text Alignment for Image Captioning	2023	Fabian Paischer Thomas Adler Markus Hofmarcher Sepp Hochreiter
+	Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning	2021	Kajetan Schweighofer Markus Hofmarcher Marius-Constantin Dinu Philipp Renz Angela Bitto-Nemling Vihang P. Patil Sepp Hochreiter
+	Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution	2021	Vihang P. Patil Markus Hofmarcher Marius-Constantin Dinu Matthias Dorfer Patrick Blies J. Brandstetter Jose A. Arjona-Medina Sepp Hochreiter
+	A Dataset Perspective on Offline Reinforcement Learning	2021	Kajetan Schweighofer Andreas Radler Marius-Constantin Dinu Markus Hofmarcher Vihang Patil Angela Bitto-Nemling Hamid Eghbal-zadeh Sepp Hochreiter
+	Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks	2020	Markus Hofmarcher Andreas Mayr Elisabeth Rumetshofer Peter Ruch Philipp Renz Johannes Schimunek Philipp Seidl Andreu Vall Michael Widrich Sepp Hochreiter
+ PDF Chat	Large-Scale Ligand-Based Virtual Screening for SARS-CoV-2 Inhibitors Using Deep Neural Networks	2020	Markus Hofmarcher Andreas Mayr Elisabeth Rumetshofer Peter Ruch Philipp Renz Johannes Schimunek Philipp Seidl Andreu Vall Michael Widrich Sepp Hochreiter
+	Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution	2020	Vihang P. Patil Markus Hofmarcher Marius-Constantin Dinu Matthias Dorfer Patrick Blies J. Brandstetter Jose A. Arjona-Medina Sepp Hochreiter
+	Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks	2020	Markus Hofmarcher Andreas Mayr Elisabeth Rumetshofer Peter Ruch Philipp Renz Johannes Schimunek Philipp Seidl Andreu Vall Michael Widrich Sepp Hochreiter
+	Patch Refinement -- Localized 3D Object Detection	2019	Johannes M. Lehner Andreas Mitterecker Thomas Adler Markus Hofmarcher Bernhard Nessler Sepp Hochreiter
+	Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images	2019	Susanne Kimeswenger Elisabeth Rumetshofer Markus Hofmarcher Philipp Tschandl Harald Kittler Sepp Hochreiter Wolfram Hötzenecker Günter Klambauer
+	Patch Refinement -- Localized 3D Object Detection	2019	Johannes M. Lehner Andreas Mitterecker Thomas Adler Markus Hofmarcher Bernhard Nessler Sepp Hochreiter

Common Coauthors

Coauthor	Papers Together
Sepp Hochreiter	16
Marius-Constantin Dinu	5
Elisabeth Rumetshofer	5
Fabian Paischer	4
Philipp Renz	4
Günter Klambauer	4
Andreu Vall	3
Michael Widrich	3
Peter Ruch	3
Johannes Schimunek	3
Vihang Patil	3
Vihang P. Patil	3
Philipp Seidl	3
Thomas Adler	3
Andreas Mitterecker	2
Kajetan Schweighofer	2
Jose A. Arjona-Medina	2
Johannes M. Lehner	2
Razvan Pascanu	2
Patrick Blies	2
Thomas Schmied	2
J. Brandstetter	2
Matthias Dorfer	2
Bernhard Nessler	2
Angela Bitto-Nemling	2
Andreas Mayr	2
Thomas Adler	1
Wolfram Hötzenecker	1
Andreas Radler	1
Susanne Kimeswenger	1
Hamid Eghbal-zadeh	1
Philipp Tschandl	1
Ajay Patel	1
Chris Callison-Burch	1
Andreas Mayr	1
Claudiu Leoveanu-Condrei	1
Harald Kittler	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Drug repositioning: identifying and developing new uses for existing drugs	2004	Ted T. Ashburn Karl B. Thor	2
+ PDF Chat	MoleculeNet: a benchmark for molecular machine learning	2017	Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes Caleb Geniesse Aneesh Pappu Karl Leswing Vijay S. Pande	2
+	Inhibition of the Main Protease 3CL-pro of the Coronavirus Disease 19 via Structure-Based Ligand Design and Molecular Modeling	2020	Marina Macchiagodena Marco Pagliai Piero Procacci	2
+ PDF Chat	Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery	2018	Kristina Preuer Philipp Renz Thomas Unterthiner Sepp Hochreiter Günter Klambauer	2
+ PDF Chat	Multi-view 3D Object Detection Network for Autonomous Driving	2017	Xiaozhi Chen Huimin Ma Ji Wan Bo Li Tian Xia	1
+ PDF Chat	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation	2017	Raffaelli Charles Hao Su Kaichun Mo Leonidas Guibas	1
+	Axiomatic Attribution for Deep Networks	2017	Mukund Sundararajan Ankur Taly Qiqi Yan	1
+	Learning from Demonstrations for Real World Reinforcement Learning	2017	Todd Hester Matej Vecerík Olivier Pietquin Marc Lanctot Tom Schaul Bilal Piot Andrew Sendonaris Gabriel Dulac-Arnold Ian Osband John Agapiou	1
+	Self-Normalizing Neural Networks	2017	Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter	1
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	1
+	Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards	2017	Matej Vecerík Todd Hester Jonathan Scholz Fumin Wang Olivier Pietquin Bilal Piot Nicolas Heess Thomas Rothörl Thomas Lampe Martin Riedmiller	1
+	Machine Learning Methods for Histopathological Image Analysis	2018	Daisuke Komura Shumpei Ishikawa	1
+ PDF Chat	Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning	2018	Ryan Poplin Avinash V. Varadarajan Katy Blumer Yun Liu Michael V. McConnell Greg S. Corrado Lily Peng Dale R. Webster	1
+	Eigenoption Discovery through the Deep Successor Representation	2017	Marlos C. Machado Clemens Rosenbaum Xiaoxiao Guo Miao Liu Gerald Tesauro Murray Campbell	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
+	Attention-based Deep Multiple Instance Learning	2018	Maximilian Ilse Jakub M. Tomczak Max Welling	1
+	Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations	2018	Xiaoqin Zhang Huimin Ma	1
+ PDF Chat	PIXOR: Real-time 3D Object Detection from Point Clouds	2018	Bin Yang Wenjie Luo Raquel Urtasun	1
+	Go-Explore: a New Approach for Hard-Exploration Problems	2019	Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune	1
+	The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors	2019	William H. Guss Mario Ynocente Castro Sam Devlin Brandon Houghton Noboru Sean Kuno Crissman Loomis Stephanie Milani Sharada P. Mohanty Keisuke Nakata Ruslan Salakhutdinov	1
+	Challenges of Real-World Reinforcement Learning	2019	Gabriel Dulac-Arnold Daniel J. Mankowitz Todd Hester	1
+	SQIL: Imitation Learning via Regularized Behavioral Cloning.	2019	Siddharth Reddy Anca D. Dragan Sergey Levine	1
+	Search-based Structured Prediction	2009	Hal Daumé John Langford Daniel Marcu	1
+ PDF Chat	PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud	2019	Shaoshuai Shi Xiaogang Wang Hongsheng Li	1
+ PDF Chat	Multi-Task Multi-Sensor Fusion for 3D Object Detection	2019	Ming Liang Bin Yang Yun Chen Rui Hu Raquel Urtasun	1
+ PDF Chat	Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving	2019	Yan Wang Wei‐Lun Chao Divyansh Garg Bharath Hariharan Mark Campbell Kilian Q. Weinberger	1
+ PDF Chat	Stereo R-CNN Based 3D Object Detection for Autonomous Driving	2019	Peiliang Li Xiaozhi Chen Shaojie Shen	1
+	A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning	2010	Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell	1
+ PDF Chat	Overcoming Exploration in Reinforcement Learning with Demonstrations	2018	Ashvin Nair Bob McGrew Marcin Andrychowicz Wojciech Zaremba Pieter Abbeel	1
+	Generative Adversarial Imitation Learning	2016	Jonathan Ho Stefano Ermon	1
+ PDF Chat	Focal Loss for Dense Object Detection	2017	Tsung-Yi Lin Priya Goyal Ross Girshick Kaiming He Piotr Dollár	1
+ PDF Chat	Joint 3D Proposal Generation and Object Detection from View Aggregation	2018	Jason S. Ku Melissa Mozifian Jungwook Lee Ali Harakeh Steven L. Waslander	1
+	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations	2018	Aravind Rajeswaran Vikash Kumar Abhishek Gupta Giulia Vezzani John Schulman Emanuel Todorov Sergey Levine	1
+	Self-Normalizing Neural Networks	2017	Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter	1
+ PDF Chat	Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks	2017	Martin Engelcke Dushyant Rao Dominic Zeng Wang Chi Hay Tong Ingmar Posner	1
+ PDF Chat	VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection	2018	Yin Zhou Oncel Tuzel	1
+	Distributional Reinforcement Learning With Quantile Regression	2017	Will Dabney Mark Rowland Marc G. Bellemare Rémi Munos	1
+ PDF Chat	Frustum PointNets for 3D Object Detection from RGB-D Data	2018	Charles R. Qi Wei Liu Chenxia Wu Hao Su Leonidas Guibas	1
+	MineRL: A Large-Scale Dataset of Minecraft Demonstrations	2019	William H. Guss Brandon Houghton Nicholay Topin Phillip Wang Cayden Codel Manuela Veloso Ruslan Salakhutdinov	1
+	Successor Options: An Option Discovery Framework for Reinforcement Learning	2019	Rahul Ramesh Manan Tomar Balaraman Ravindran	1
+ PDF Chat	PointPillars: Fast Encoders for Object Detection From Point Clouds	2019	Alex Lang Sourabh Vora Holger Caesar Lubing Zhou Jiong Yang Oscar Beijbom	1
+ PDF Chat	RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement	2019	Kiwoo Shin Youngwook Paul Kwon Masayoshi Tomizuka	1
+	Experience Replay for Continual Learning	2019	David Rolnick Arun Ahuja Jonathan Schwarz Timothy Lillicrap Gregory Wayne	1
+	RUDDER: Return Decomposition for Delayed Rewards	2019	Jose A. Arjona-Medina Michael Gillhofer Michael Widrich Thomas Unterthiner J. Brandstetter Sepp Hochreiter	1
+	Search on the Replay Buffer: Bridging Planning and Reinforcement Learning	2019	Benjamin Eysenbach Ruslan Salakhutdinov Sergey Levine	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+	Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction	2019	Aviral Kumar Justin Fu Matthew Soh George Tucker Sergey Levine	1
+	Hierarchical Deep Q-Network with Forgetting from Imperfect Demonstrations in Minecraft.	2019	Alexey Skrynnik Aleksey Staroverov Ermek Aitygulov Kirill Aksenov Vasilii Davydov Aleksandr I. Panov	1
+	Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards	2020	Allan Zhou Eric Jang Daniel Kappler Alex Herzog Mohi Khansari Paul Wohlhart Yunfei Bai Mrinal Kalakrishnan Sergey Levine Chelsea Finn	1
+ PDF Chat	Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance	2020	Mingxuan Jing Xiaojian Ma Wenbing Huang Fuchun Sun Chao Yang Bin Fang Huaping Liu	1