Andreas Krause

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 410

Top Venues

Publications

Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning. IEEE Robotics Autom. Lett. 9 (4) (2024)
Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause
Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction. CoRR (2024)
Daniel Robert-Nicoud, Andreas Krause, Viacheslav Borovitskiy
Intrinsic Gaussian Vector Fields on Manifolds. AISTATS (2024)
Jiawei Huang, Niao He, Andreas Krause
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL. CoRR (2024)
Manish Prajapat, Mojmir Mutny, Melanie N. Zeilinger, Andreas Krause
Submodular Reinforcement Learning. ICLR (2024)
Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný
Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR (2024)
Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
NeoRL: Efficient Exploration for Nonepisodic RL. CoRR (2024)
Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause
Adversarial Causal Bayesian Optimization. ICLR (2024)
Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause
Bridging the Sim-to-Real Gap with Bayesian Inference. CoRR (2024)
Lenart Treven, Bhavya Sukhija, Yarden As, Florian Dörfler, Andreas Krause
When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL. CoRR (2024)
Vinzenz Thoma, Barna Pasztor, Andreas Krause, Giorgia Ramponi, Yifan Hu
Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes. CoRR (2024)
Manish Prajapat, Johannes Köhler, Matteo Turchetta, Andreas Krause, Melanie N. Zeilinger
Safe Guaranteed Exploration for Non-linear Systems. CoRR (2024)
Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause
Information-based Transductive Active Learning. CoRR (2024)
Barna Pásztor, Parnian Kassraie, Andreas Krause
Bandits with Preference Feedback: A Stackelberg Game Perspective. CoRR (2024)
Lars Lorch, Andreas Krause, Bernhard Schölkopf
Causal Modeling with Stationary Diffusions. AISTATS (2024)
Yarden As, Bhavya Sukhija, Andreas Krause
Safe Exploration Using Bayesian World Models and Log-Barrier Optimization. CoRR (2024)
Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces. AISTATS (2024)
Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause
Provably Learning Nash Policies in Constrained Markov Potential Games. AAMAS (2024)
Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause
Standardizing Structural Causal Models. CoRR (2024)
Riccardo De Santi, Manish Prajapat, Andreas Krause
Global Reinforcement Learning: Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods. CoRR (2024)
Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause
Active Few-Shot Fine-Tuning. CoRR (2024)
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
Learning Safety Constraints from Demonstrations with Unknown Rewards. AISTATS (2024)
Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. AAMAS (2024)
Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm. AISTATS (2024)
Max B. Paulus, Andreas Krause
Learning To Dive In Branch And Bound. NeurIPS (2023)
Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRR (2023)
Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. CoRR (2023)
Christopher Koenig, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan
Safe Risk-averse Bayesian Optimization for Controller Tuning. CoRR (2023)
Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
Stochastic Approximation Algorithms for Systems of Interacting Particles. NeurIPS (2023)
Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier
Leveraging Demonstrations with Latent Space Priors. Trans. Mach. Learn. Res. 2023 (2023)
Vignesh Ram Somnath, Pier Giuseppe Sessa, María Rodríguez Martínez, Andreas Krause
DockGame: Cooperative Games for Multimeric Rigid Protein Docking. CoRR (2023)
Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause
Isotropic Gaussian Processes on Finite Spaces of Graphs. AISTATS (2023)
Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos
Riemannian stochastic optimization methods avoid strict saddle points. NeurIPS (2023)
Felix Berkenkamp, Andreas Krause, Angela P. Schoellig
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics. Mach. Learn. 112 (10) (2023)
Johannes Kirschner, Tor Lattimore, Andreas Krause
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications. CoRR (2023)
Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning. CoRR (2023)
Ali Gorji, Andisheh Amrollahi, Andreas Krause
A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks. UAI (2023)
Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn
Contextual Stochastic Bilevel Optimization. NeurIPS (2023)
Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
Sinkhorn Flow: A Continuous-Time Framework for Understanding and Generalizing the Sinkhorn Algorithm. CoRR (2023)
Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano
Anytime Model Selection in Linear Bandits. NeurIPS (2023)
Bhavya Sukhija, Nathanael Köhler, Miguel Zamora, Simon Zimmermann, Sebastian Curi, Andreas Krause, Stelian Coros
Gradient-Based Trajectory Optimization With Learned Dynamics. ICRA (2023)
Barna Pásztor, Andreas Krause, Ilija Bogunovic
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. NeurIPS (2023)
Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRL (2023)
Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli
Unbalanced Diffusion Schrödinger Bridge. CoRR (2023)
Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause
Provably Learning Nash Policies in Constrained Markov Potential Games. CoRR (2023)
Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS (2023)
Parnian Kassraie, Aldo Pacchiano, Nicolas Emmenegger, Andreas Krause
Anytime Model Selection in Linear Bandits. CoRR (2023)
Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artif. Intell. 320 (2023)
Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation. CoRR (2023)
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR (2023)
Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dörfler, Andreas Krause
Efficient Exploration in Continuous-time Model-based Reinforcement Learning. NeurIPS (2023)
Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne
Aligned Diffusion Schrödinger Bridges. UAI (2023)
Nicolas Emmenegger, Mojmír Mutný, Andreas Krause
Likelihood Ratio Confidence Sets for Sequential Decision Making. CoRR (2023)
Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause
MARS: Meta-learning as Score Matching in the Function Space. ICLR (2023)
Scott Sussex, Anastasia Makarova, Andreas Krause
Model-based Causal Bayesian Optimization. ICLR (2023)
Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause
Model-based Causal Bayesian Optimization. CoRR (2023)
Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause
Hallucinated adversarial control for conservative offline policy evaluation. UAI (2023)
Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne
Aligned Diffusion Schrödinger Bridges. CoRR (2023)
Ali Gorji, Andisheh Amrollahi, Andreas Krause
A Scalable Walsh-Hadamard Regularizer to Overcome the Low-degree Spectral Bias of Neural Networks. CoRR (2023)
Max B. Paulus, Andreas Krause
Learning To Dive In Branch And Bound. CoRR (2023)
Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause
Incentive-Compatible Forecasting Competitions. Manag. Sci. 69 (3) (2023)
Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic
Near-optimal Policy Identification in Active Reinforcement Learning. ICLR (2023)
Christopher König, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan
Safe Risk-Averse Bayesian Optimization for Controller Tuning. IEEE Robotics Autom. Lett. 8 (12) (2023)
Mojmir Mutny, Tadeusz Janik, Andreas Krause
Active Exploration via Experiment Design in Markov Chains. AISTATS (2023)
Nicolas Emmenegger, Mojmir Mutny, Andreas Krause
Likelihood Ratio Confidence Sets for Sequential Decision Making. NeurIPS (2023)
Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces. CoRR (2023)
Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause
Optimistic Active Exploration of Dynamical Systems. CoRR (2023)
Ya-Ping Hsieh, Mohammad Reza Karimi, Andreas Krause, Panayotis Mertikopoulos
Riemannian stochastic optimization methods avoid strict saddle points. CoRR (2023)
Lars Lorch, Andreas Krause, Bernhard Schölkopf
Causal Modeling with Stationary Diffusions. CoRR (2023)
Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
A Dynamical System View of Langevin-Based Non-Convex Sampling. NeurIPS (2023)
Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dörfler, Andreas Krause
Efficient Exploration in Continuous-time Model-based Reinforcement Learning. CoRR (2023)
Manish Prajapat, Mojmír Mutný, Melanie N. Zeilinger, Andreas Krause
Submodular Reinforcement Learning. CoRR (2023)
Daniel Robert-Nicoud, Andreas Krause, Viacheslav Borovitskiy
Intrinsic Gaussian Vector Fields on Manifolds. CoRR (2023)
Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. CoRR (2023)
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
Replicable Bandits. ICLR (2023)
Bernardo Fichera, Viacheslav Borovitskiy, Andreas Krause, Aude Billard
Implicit Manifold Gaussian Process Regression. CoRR (2023)
Bernardo Fichera, Slava Borovitskiy, Andreas Krause, Aude Gemma Billard
Implicit Manifold Gaussian Process Regression. NeurIPS (2023)
Yunke Ao, Hooman Esfandiari, Fabio Carrillo, Yarden As, Mazda Farshad, Benjamin F. Grewe, Andreas Krause, Philipp Fürnstahl
Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement. CoRR (2023)
Puck van Gerwen, Ksenia R. Briling, Charlotte Bunne, Vignesh Ram Somnath, Rubén Laplaza, Andreas Krause, Clémence Corminboeuf
EquiReact: An equivariant neural network for chemical reactions. CoRR (2023)
Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause
The Schrödinger Bridge between Gaussian Measures has a Closed Form. AISTATS (2023)
Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause
Lifelong bandit optimization: no prior and no regret. UAI (2023)
Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause
Optimistic Active Exploration of Dynamical Systems. NeurIPS (2023)
Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn
Contextual Stochastic Bilevel Optimization. CoRR (2023)
Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M. Buhmann, Andreas Krause
Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS (2022)
Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
Active Bayesian Causal Inference. CoRR (2022)
Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause
The Dynamics of Riemannian Robbins-Monro Algorithms. CoRR (2022)
Scott Sussex, Anastasiia Makarova, Andreas Krause
Model-based Causal Bayesian Optimization. CoRR (2022)
Mojmir Mutny, Andreas Krause
Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS (2022)
Charlotte Bunne, Andreas Krause, Marco Cuturi
Supervised Training of Conditional Monge Maps. CoRR (2022)
Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause
PAC-Bayesian Meta-Learning: From Theory to Practice. CoRR (2022)
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
Interactively Learning Preference Constraints in Linear Bandits. CoRR (2022)
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
Interactively Learning Preference Constraints in Linear Bandits. ICML (2022)
Jonas Rothfuss, Christopher Koenig, Alisa Rupenyan, Andreas Krause
Meta-Learning Priors for Safe Bayesian Optimization. CoRL (2022)
Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR (2022)
Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization. CoRR (2022)
Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause
MARS: Meta-Learning as Score Matching in the Function Space. CoRR (2022)
Mathieu Chevalley, Charlotte Bunne, Andreas Krause, Stefan Bauer
Invariant Causal Mechanisms through Distribution Matching. CoRR (2022)
Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning. CoRR (2022)
David Lindner, Andreas Krause, Giorgia Ramponi
Active Exploration for Inverse Reinforcement Learning. CoRR (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Andreas Krause