Schölkopf, Bernhard

Estimating the Support of a High-Dimensional Distribution

Schölkopf, B., Platt, J. C., Shawe-Taylor, J., Smola, A. J., & Williamson, R. C. (2001) · Neural Computation

Machine Learning and AlgorithmsNeural Networks and Applications

Cited by 6,168

A Kernel Method for the Two-Sample-Problem

Gretton, A., Borgwardt, K. M., Rasch, M., Schölkopf, B., & Smola, A. J. (2007) · Advances in Neural Information Processing Systems 19

Probability and Statistical ResearchStatistical Methods and Applications

Cited by 2,167

Integrating structured biological data by Kernel Maximum Mean Discrepancy

Borgwardt, K. M., Gretton, A., Rasch, M. J., Kriegel, H.-P., Schölkopf, B., & Smola, A. J. (2006) · Bioinformatics

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 1,674

Domain Generalization via Invariant Feature Representation

Muandet, K., Balduzzi, D., & Schölkopf, B. (2013) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 771

Learning to Deblur

Schuler, C. J., Hirsch, M., Harmeling, S., & Schölkopf, B. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Image Processing TechniquesImage Processing Techniques and Applications

Cited by 560

Avoiding Discrimination through Causal Reasoning

Kilbertus, N., Rojas-Carulla, M., Parascandolo, G., Hardt, M., Janzing, D., & Schölkopf, B. (2017) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 358

A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations

Karimi, A.-H., Barthe, G., Schölkopf, B., & Valera, I. (2023) · ACM Computing Surveys

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 301

Algorithmic recourse: From counterfactual explanations to interventions

Karimi, A.-H., Schölkopf, B., & Valera, I. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 274

Unifying distillation and privileged information

Lopez-Paz, D., Bottou, L., Schölkopf, B., & Vapnik, V. (2015) · arXiv

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 270

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation

Kim, J., Tabibian, B., Oh, A., Schölkopf, B., & Gomez-Rodriguez, M. (2018) · Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

Misinformation and Its ImpactsComplex Network Analysis Techniques

Cited by 230

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0

O’Neill, A., Rehman, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., Mandlekar, A., Jain, A., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 210

Probabilistic movement modeling for intention inference in human–robot interaction

Wang, Z., Mülling, K., Deisenroth, M. P., Ben Amor, H., Vogt, D., Schölkopf, B., & Peters, J. (2013) · The International Journal of Robotics Research

Social Robot Interaction and HRIAction Observation and Synchronization

Cited by 171

Evaluating Predictive Uncertainty Challenge

Quiñonero-Candela, J., Rasmussen, C. E., Sinz, F., Bousquet, O., & Schölkopf, B. (2006) · Lecture Notes in Computer Science

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 116

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Embodiment Collaboration, O'Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 111

Algorithmic Recourse: from Counterfactual Explanations to Interventions

Karimi, A.-H., Schölkopf, B., & Valera, I. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 76

On the Fairness of Causal Algorithmic Recourse

Kügelgen, J. V., Karimi, A.-H., Bhatt, U., Valera, I., Weller, A., & Schölkopf, B. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 58

Logical Fallacy Detection

Jin, Z., Lalwani, A., Vaidhya, T., Shen, X., Ding, Y., Lyu, Z., Sachan, M., Mihalcea, R., & Schölkopf, B. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Linguistics and Discourse AnalysisTopic Modeling

Cited by 52

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O., Träuble, F., Goyal, A., Neitz, A., Bengio, Y., Schölkopf, B., Wüthrich, M., & Bauer, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 50

CLadder: Assessing Causal Reasoning in Language Models

Jin, Z., Chen, Y., Leeb, F., Gresele, L., Kamal, O., Lyu, Z., Blin, K., Adauto, F. G., Kleiman-Weiner, M., Sachan, M., et al. (2023) · Advances in Neural Information Processing Systems 36

Logic, Reasoning, and KnowledgeBayesian Modeling and Causal Inference

Cited by 19

International AI Safety Report

Bengio, Y., Mindermann, S., Privitera, D., Besiroglu, T., Bommasani, R., Casper, S., Choi, Y., Fox, P., Garfinkel, B., Goldfarb, D., et al. (2025) · arXiv

Ethics and Social Impacts of AISafety Systems Engineering in Autonomy

Cited by 16

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents

Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024) · Advances in Neural Information Processing Systems 37

Evolutionary Game Theory and CooperationMulti-Agent Systems and Negotiation

Cited by 14

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents

Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024) · arXiv

Evolutionary Game Theory and CooperationMulti-Agent Systems and Negotiation

Cited by 14

Towards causal algorithmic recourse

Karimi, A.-H., von Kügelgen, J., Schölkopf, B., & Valera, I. (2022) · Lecture Notes in Computer Science

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 11

CLadder: Assessing Causal Reasoning in Language Models

Jin, Z., Chen, Y., Leeb, F., Gresele, L., Kamal, O., Lyu, Z., Blin, K., Adauto, F. G., Kleiman-Weiner, M., Sachan, M., et al. (2023) · arXiv

Logic, Reasoning, and KnowledgeBayesian Modeling and Causal Inference

Cited by 8