Bernhard Schölkopf

Computer Science · Physical Sciences

141h-index145.4kcitations1.5kworks3.42yr avg
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Research Topics

Neural Networks and Applications(203), Bayesian Modeling and Causal Inference(139), Face and Expression Recognition(125), Machine Learning and Algorithms(99), Gaussian Processes and Bayesian Inference(89)

Publications1.5k total

Position: Science is Collaborative-LLM for Science Should Be Too
2026Open Access
Natural language processing
Edward Elgar Publishing eBooks·2025
Scaling Behavior of Discrete Diffusion Language Models
arXiv (Cornell University)·2025Open Access
Generation is Required for Data-Efficient Perception
arXiv (Cornell University)·2025Open Access
International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management
SuperIntelligence - Robotics - Safety & Alignment·2025
Borges and AI
Libreria Editrice Vaticana eBooks·2025
Flexible Gravitational-Wave Parameter Estimation with Transformers
arXiv (Cornell University)·2025Open Access
Are LLMs Good Safety Agents or a Propaganda Engine?
arXiv (Cornell University)·2025Open Access
International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management
ArXiv.org·2025Open Access
Tracing Multilingual Representations in LLMs with Cross-Layer Transcoders
arXiv (Cornell University)·2025Open Access
TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
arXiv (Cornell University)·2025Open Access
Natural Building Blocks for Structured World Models: Theory, Evidence, and Scaling
arXiv (Cornell University)·2025Open Access
International Al Safety Report: First Key Update Capabilities and Risk Implications
SuperIntelligence - Robotics - Safety & Alignment·2025Open Access
Cultural Alien Sampler: Open-ended art generation balancing originality and coherence
arXiv (Cornell University)·2025Open Access
Collective Intelligence: On the Promise and Reality of Multi-Agent Systems for AI-Driven Scientific Discovery
Preprints.org·2025· 1 citedOpen Access
In silico biological discovery with large perturbation models
Nature Computational Science·2025· 2 citedOpen Access
International AI Safety Report 2025: First Key Update: Capabilities and Risk Implications
arXiv (Cornell University)·2025· 1 citedOpen Access
Collective Intelligence: On the Promise and Reality of Multi-Agent Systems for AI-Driven Scientific Discovery
Preprints.org·2025Open Access
PENEX: AdaBoost-Inspired Neural Network Regularization
arXiv (Cornell University)·2025Open Access
Physics of Learning: A Lagrangian perspective to different learning paradigms
arXiv (Cornell University)·2025Open Access
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Frequent Co-authors

Alex Smola(11), Gunnar Rätsch(9), Alexander J. Smola(8), Arthur Gretton(8), Jason Weston(5), Klaus‐Robert Müller(4), Olivier Bousquet(4), John Platt(3), Robert C. Williamson(3), Dengyong Zhou(3), K. Müller(3), Mika Sirén(3), Karsten Borgwardt(3), Malte J. Rasch(3), Vladimir Vapnik(3), Jonas Peters(3), Christopher J. C. Burges(2), John Shawe‐Taylor(2), Detlef Weigel(2), Chris Burges(2)