Empirical Inference


2024


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Latent Diffusion for Neural Spiking Data

Kapoor, J., Schulz, A., Vetter, J., Pei, F., Gao, R., Macke, J. H.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

2024

[BibTex]


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Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving

Didolkar, A. R., Goyal, A., Ke, N. R., Guo, S., Valko, M., Lillicrap, T. P., Rezende, D. J., Bengio, Y., Mozer, M. C., Arora, S.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Learning partitions from Context

Buchholz, S.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Causal vs. Anticausal merging of predictors

Garrido, S., Blöbaum, P., Schölkopf, B., Janzing, D.

In Advances in Neural Information Processing Systems 37 (NeurIPS 2024) , 38th Annual Conference on Neural Information Processing Systems, December 2024 (inproceedings) Accepted

[BibTex]

[BibTex]


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A Generative Model of Symmetry Transformations

Allingham, J. U., Mlodozeniec, B. K., Padhy, S., Antoran, J., Krueger, D., Turner, R. E., Nalisnick, E., Hernández-Lobato, J. M.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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From Causal to Concept-Based Representation Learning

Rajendran*, G., Buchholz*, S., Aragam, B., Schölkopf, B., Ravikumar, P. K.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks

Zhao, J., Singh, S. P., Lucchi, A.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Robust Mixture Learning when Outliers Overwhelm Small Groups

Dmitriev, D., Buhai, R., Tiegel, S., Wolters, A., Novikov, G., Sanyal, A., Steurer, D., Yang, F.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks

Chen, W., Ge, H.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024) , 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes

Lin, J. A., Padhy, S., Mlodozeniec, B. K., Antoran, J., Hernández-Lobato, J. M.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024) , 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Cooperate or Collapse: Emergence of Sustainability in a Society of LLM Agents

Piatti*, G., Jin*, Z., Kleiman-Weiner*, M., Schölkopf, B., Sachan, M., Mihalcea, R.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024, *equal contribution (conference) Accepted

[BibTex]

[BibTex]


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Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation

Vetter, J., Moss, G., Schröder, C., Gao, R., Macke, J. H.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study

Jain, S., Lubana, E. S., Oksuz, K., Joy, T., Torr, P., Sanyal, A., Dokania, P. K.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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On Affine Homotopy between Language Encoders

Chan, R., Bourmasmoud, R., Svete, A., Ren, Y., Guo, Q., Jin, Z., Ravfogel, S., Sachan, M., Schölkopf, B., El-Assady, M., Cotterell, R.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Inferring stochastic low-rank recurrent neural networks from neural data

Pals, M., Sağtekin, A. E., Pei, F., Gloeckler, M., Macke, J.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024) , 38th Annual Conference on Neural Information Processing Systems, December 2024 (conference) Accepted

[BibTex]

[BibTex]


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Do Finetti: On Causal Effects for Exchangeable Data

Guo, S., Zhang, C., Muhan, K., Huszár*, F., Schölkopf*, B.

Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38th Annual Conference on Neural Information Processing Systems, December 2024, *joint senior authors (conference) Accepted

[BibTex]

[BibTex]


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Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips

Andrussow, I., Sun, H., Martius, G., Kuchenbecker, K. J.

Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

Abstract
Beyond vision and hearing, tactile sensing enhances a robot's ability to dexterously manipulate unfamiliar objects and safely interact with humans. Giving touch sensitivity to robots requires compact, robust, affordable, and efficient hardware designs, especially for high-resolution tactile sensing. We present a soft vision-based tactile sensor engineered to meet these requirements. Comparable in size to a human fingertip, Minsight uses machine learning to output high-resolution directional contact force distributions at 60 Hz. Minsight's tactile force maps enable precise sensing of fingertip contacts, which we use in this hands-on demonstration to allow a 3-DoF robot arm to physically track contact with a user's finger. While observing the colorful image captured by Minsight's internal camera, attendees can experience how its ability to detect delicate touches in all directions facilitates real-time robot interaction.

Project Page [BibTex]

Project Page [BibTex]


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Fiber-Optic Shape Sensing Using Neural Networks Operating on Multispecklegrams

Cao, C. G. L., Javot, B., Bhattarai, S., Bierig, K., Oreshnikov, I., Volchkov, V. V.

IEEE Sensors Journal, 24(17):27532-27540, September 2024 (article)

Abstract
Application of machine learning techniques on fiber speckle images to infer fiber deformation allows the use of an unmodified multimode fiber to act as a shape sensor. This approach eliminates the need for complex fiber design or construction (e.g., Bragg gratings and time-of-flight). Prior work in shape determination using neural networks trained on a finite number of possible fiber shapes (formulated as a classification task), or trained on a few continuous degrees of freedom, has been limited to reconstruction of fiber shapes only one bend at a time. Furthermore, generalization to shapes that were not used in training is challenging. Our innovative approach improves generalization capabilities, using computer vision-assisted parameterization of the actual fiber shape to provide a ground truth, and multiple specklegrams per fiber shape obtained by controlling the input field. Results from experimenting with several neural network architectures, shape parameterization, number of inputs, and specklegram resolution show that fiber shapes with multiple bends can be accurately predicted. Our approach is able to generalize to new shapes that were not in the training set. This approach of end-to-end training on parameterized ground truth opens new avenues for fiber-optic sensor applications. We publish the datasets used for training and validation, as well as an out-of-distribution (OOD) test set, and encourage interested readers to access these datasets for their own model development.

DOI [BibTex]


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Learning to Control Emulated Muscles in Real Robots: Towards Exploiting Bio-Inspired Actuator Morphology

Schumacher, P., Krause, L., Schneider, J., Büchler, D., Martius, G., Haeufle, D.

In 10th International Conference on Biomedical Robotics and Biomechatronics (BioRob), September 2024 (inproceedings) Accepted

arXiv [BibTex]

arXiv [BibTex]


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Advances in Probabilistic Methods for Deep Learning

Immer, A.

ETH Zurich, Switzerland, September 2024, CLS PhD Program (phdthesis)

[BibTex]

[BibTex]


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A Probabilistic Model behind Self-Supervised Learning

Bizeul, A., Schölkopf, B., Allen, C.

Transactions on Machine Learning Research, September 2024 (article) To be published

PDF [BibTex]

PDF [BibTex]


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Moûsai: Efficient Text-to-Music Diffusion Models

Schneider, F., Kamal, O., Jin, Z., Schölkopf, B.

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Volume 1: Long Papers, pages: 8050-8068, (Editors: Lun-Wei Ku and Andre Martins and Vivek Srikumar), Association for Computational Linguistics, August 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Modelling Variability in Human Annotator Simulation

Wu*, W., Chen*, W., Zhang, C., Woodland, P. C.

Findings of the Association for Computational Linguistics (ACL), pages: 1139-1157, (Editors: Ku, Lun-Wei and Martins, Andre and Srikumar, Vivek), Association for Computational Linguistics, August 2024, *equal contribution (conference)

link (url) [BibTex]

link (url) [BibTex]


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Competition of Mechanisms: Tracing How Language Models Handle Facts and Counterfactuals

Ortu*, F., Jin*, Z., Doimo, D., Sachan, M., Cazzaniga, A., Schölkopf, B.

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) , Volume 1, Long Papers, pages: 8420-8436, (Editors: Lun-Wei Ku and Andre Martins and Vivek Srikumar), Association for Computational Linguistics, August 2024, *equal contribution (conference)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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CausalCite: A Causal Formulation of Paper Citations

Kumar, I., Jin, Z., Mokhtarian, E., Guo, S., Chen, Y., Kiyavash, N., Sachan, M., Schölkopf, B.

Findings of the Association for Computational Linguistics (ACL), pages: 8395-8410, (Editors: Ku, Lun-Wei and Martins, Andre and Srikumar, Vivek), Association for Computational Linguistics, August 2024 (conference)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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Leveraging Task Structures for Improved Identifiability in Neural Network Representations

Chen*, W., Horwood*, J., Heo, J., Hernández-Lobato, J. M.

Transactions on Machine Learning Research, August 2024, *equal contribution (article)

link (url) [BibTex]

link (url) [BibTex]


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On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective

Dmitriev, D., Szabó, K., Sanyal, A.

Proceedings of the 37th Annual Conference on Learning Theory (COLT), 247, pages: 1379-1398, Proceedings of Machine Learning Research, (Editors: Agrawal, Shipra and Roth, Aaron), PMLR, July 2024, (talk) (conference)

link (url) [BibTex]

link (url) [BibTex]


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Robustness of Nonlinear Representation Learning

Buchholz, S., Schölkopf, B.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 4785-4821, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for ODEs

Beck, J., Bosch, N., Deistler, M., Kadhim, K. L., Macke, J. H., Hennig, P., Berens, P.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 3305-3326, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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Simultaneous identification of models and parameters of scientific simulators

Schröder, C., Macke, J. H.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 43895-43927, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Position: Understanding LLMs Requires More Than Statistical Generalization

Reizinger, P., Ujváry, S., Mészáros, A., Kerekes, A., Brendel, W., Huszár, F.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 42365-42390, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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Diffusive Gibbs Sampling

Chen*, W., Zhang*, M., Paige, B., Hernández-Lobato, J. M., Barber, D.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 7731-7747, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024, *equal contribution (conference)

link (url) [BibTex]

link (url) [BibTex]


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What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study

Jain, S., Lubana, E. S., Oksuz, K., Joy, T., Torr, P. H. S., Sanyal, A., Dokania, P. K.

ICML 2024 Workshop on Mechanistic Interpretability (Spotlight), July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Improving Neural Additive Models with Bayesian Principles

Bouchiat, K., Immer, A., Yèche, H., Rätsch, G., Fortuin, V.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 4416-4443, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Unveiling CLIP Dynamics: Linear Mode Connectivity and Generalization

Abdolahpourrostam, A., Sanyal, A., Moosavi-Dezfooli, S.

ICML 2024 Workshop on Foundation Models in the Wild, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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A Sparsity Principle for Partially Observable Causal Representation Learning

Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., Magliacane, S.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 55389-55433, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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A Measure-Theoretic Axiomatisation of Causality and Kernel Regression

Park, J.

University of Tübingen, Germany, July 2024 (phdthesis)

[BibTex]

[BibTex]


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Geometry-Aware Instrumental Variable Regression

Kremer, H., Schölkopf, B.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 25560-25582, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Targeted Reduction of Causal Models

Kekić, A., Schölkopf, B., Besserve, M.

40th Conference on Uncertainty in Artificial Intelligence (UAI), July 2024 (conference) To be published

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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Stitching Manifolds: Leveraging Interaction to Compose Object Representations into Scenes

Keurti, H., Schölkopf, B., Aceituno, P. V., Grewe, B.

ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM), July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Provable Privacy with Non-Private Pre-Processing

Hu, Y., Sanyal, A., Schölkopf, B.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 19402-19437, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Implicit meta-learning may lead language models to trust more reliable sources

Krasheninnikov, D., Krasheninnikov, E., Mlodozeniec, Bruno K., Maharaj, T., Krueger, D.

Proceedings of the 41st International Conference on Machine Learning, 235, pages: 25534-25559, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Products, Abstractions and Inclusions of Causal Spaces

Buchholz, S., Park, J., Schölkopf, B.

40th Conference on Uncertainty in Artificial Intelligence (UAI), July 2024 (conference) To be published

arXiv [BibTex]

arXiv [BibTex]


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Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?

Opedal, A., Stolfo, A., Shirakami, H., Jiao, Y., Cotterell, R., Schölkopf, B., Saparov, A., Sachan, M.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 38762-38778, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Detecting and Identifying Selection Structure in Sequential Data

Zheng, Y., Tang, Z., Qiu, Y., Schölkopf, B., Zhang, K.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 61498-61525, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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The Role of Learning Algorithms in Collective Action

Ben-Dov*, O., Fawkes*, J., Samadi, S., Sanyal, A.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 3443-3461, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024, *equal contribution (conference)

link (url) [BibTex]

link (url) [BibTex]


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All-in-one simulation-based inference

Gloeckler, M., Deistler, M., Weilbach, C. D., Wood, F., Macke, J. H.

Proceedings of the 41st International Conference on Machine Learning (ICML), 235, pages: 15735-15766, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Deep Backtracking Counterfactuals for Causally Compliant Explanations

Kladny, K., Kügelgen, J. V., Schölkopf, B., Muehlebach, M.

Transactions on Machine Learning Research, July 2024 (article)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]