Krause, Andreas
305 publications
ICLR
2025
MaxInfoRL: Boosting Exploration in Reinforcement Learning Through Information Gain Maximization
ICLR
2025
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
NeurIPS
2025
SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound
JMLR
2024
Log Barriers for Safe Black-Box Optimization with Application to Safe Reinforcement Learning
ICMLW
2024
Reinforcement Learning from Human Text Feedback: Learning a Reward Model from Human Text Input
AISTATS
2024
Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm
UAI
2023
A Scalable Walsh-Hadamard Regularizer to Overcome the Low-Degree Spectral Bias of Neural Networks
MLJ
2023
Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics
JMLR
2023
Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications
NeurIPSW
2023
Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design
JMLR
2023
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
AISTATS
2022
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes
ICML
2022
Efficient Model-Based Multi-Agent Reinforcement Learning via Optimistic Equilibrium Computation
ICML
2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
L4DC
2021
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory
NeurIPS
2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
ICML
2021
Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
NeurIPS
2021
Robust Generalization Despite Distribution Shift via Minimum Discriminating Information
NeurIPS
2020
Efficient Model-Based Reinforcement Learning Through Optimistic Policy Search and Planning
ICML
2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
AAAI
2020
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
AISTATS
2019
Bounding Inefficiency of Equilibria in Continuous Actions Games Using Submodularity and Curvature
AISTATS
2019
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs
ICML
2019
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
IJCAI
2019
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning
NeurIPS
2018
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
AAAI
2018
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints
AAAI
2018
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly
CoRL
2018
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems
ICML
2017
Deletion-Robust Submodular Maximization: Data Summarization with “the Right to Be Forgotten”
AISTATS
2016
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures
NeurIPS
2016
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
NeurIPS
2013
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data
ICML
2012
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization