Prof. Andreas Krause — Research Profile
ETH Zurich · Department of Computer Science
About
취리히 연방공과대학교 컴퓨터과학과 소속 Andreas Krause 교수의 등록된 연구 분야는 machine learning, artificial intelligence, reinforcement learning, probabilistic inference입니다.
Research keywords
Recent papers
- VioLA: Learning Generalist Humanoid Control Policies from Human DataNewPreprintarXiv (Cornell University) · Oct 8
- Task Vector Descent: Learning from Non-IID BatchesNewPreprintarXiv (Cornell University) · Oct 4
- Tactile Curiosity Drives Robot InteractionNewPreprintarXiv (Cornell University) · Sep 30
From OpenAlex · papers whose author affiliation matches this university
Labs doing related research
Labs that recently published on topics this lab's recent papers share
Marco Hutter 교수 연구실
ETH Zurich · Department of Mechanical and Process Engineering
Bidirectional Voronoi-biased Exploration Curriculum for Reinforcement LearningNewPreprintarXiv (Cornell University) · Oct 2Shared topic: Reinforcement Learning in Robotics
Antoine Bosselut 교수 연구실
EPFL · School of Computer and Communication Sciences
Learning What to Imitate: Entropy-Aware Distribution MixingPreprintarXiv (Cornell University) · Oct 5Shared topic: Domain Adaptation and Few-Shot Learning
Martin Jaggi 교수 연구실
EPFL · School of Computer and Communication Sciences
Adapting English Quality Classifiers for Multilingual LLM Pretraining Data SelectionPreprintarXiv (Cornell University) · Oct 8Shared topic: Topic Modeling
Other labs in this department
- Adrian Perrig 교수 연구실
system and network security, networks, internet architecture
- Ana Klimovic 교수 연구실
cloud computing, operating systems, distributed systems, storage systems, computer architecture
- Angelika Steger 교수 연구실
algorithms, combinatorics, randomization and probabilistic methods, combinatorial models for optimization
- April Yi Wang 교수 연구실
educational technology, human-computer interaction, artificial intelligence in education, collective intelligence and organizational technology, end-user programming, user interface for programming
- Bernhard Schölkopf 교수 연구실
machine learning, causal inference, applications in the sciences
- Christian Holz 교수 연구실
virtual reality, healthcare, ubiquitous computing, embedded systems, haptics, human-computer interaction, physical prototyping, sensing, signal processing, predictive health