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We are conducting theoretical, algorithmic, and experimental studies to advance study of empirical inference.

Die Mitglieder der Abteilung „Empirische Inferenz“ widmen sich dem Maschinellen Lernen und der Kausalen Inferenz. Sie entwickeln Algorithmen, die selbstständig Regelmäßigkeiten in Daten erkennen und daraus Schlussfolgerungen ziehen. Das primäre Ziel der Forscher*innen ist, zu verstehen, wie Lebewesen und künstliche Systeme Strukturen erkennen, um damit in der Welt zu agieren. Sie wollen dazu beitragen, dass die theoretischen Methoden des Maschinellen Lernens z.B. in der Medizin oder Astronomie Anwendung finden.

Director
Bernhard Schölkopf

Bernhard Schölkopf

  • Director
Admin Team
Sabrina Rehbaum

Sabrina Rehbaum

Personal Assistant
+49 7071 601 551
sekretariat-schoelkopf@tuebingen.mpg.de

Department Highlights

News Empirical Inference 2025-03-06

Neural network deciphers gravitational waves from merging neutron stars in a second

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Publication Empirical Inference 2025-03-01

Real-time inference for binary neutron star mergers using machine learning

Publication Empirical Inference 2025-01-01

Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels

Publication Empirical Inference 2024-12-01

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

Publication Empirical Inference 2024-12-01

Do Finetti: On Causal Effects for Exchangeable Data

Publication Empirical Inference 2024-12-01

From Causal to Concept-Based Representation Learning

Publication Empirical Inference 2024-12-01

Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias

Publication Empirical Inference 2024-12-01

Shaving Weights with Occam’s Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood

Publication Empirical Inference 2024-11-01

The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning

Publication Empirical Inference 2024-11-01

Do LLMs Think Fast and Slow? A Causal Study on Sentiment Analysis

Publication Empirical Inference 2024-11-01

Diffusion-based learning of contact plans for agile locomotion

Publication Empirical Inference 2024-11-01

Implicit Personalization in Language Models: A Systematic Study

Publication Empirical Inference 2024-10-01

Redesigning Information Markets in the Era of Language Models

Publication Empirical Inference 2024-08-01

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

Publication Empirical Inference 2024-08-01

CausalCite: A Causal Formulation of Paper Citations

Publication Empirical Inference 2024-08-01

Moûsai: Efficient Text-to-Music Diffusion Models

News Empirical Inference 2024-07-15

Siyuan Guo wins 2024 MPI-IS Outstanding Female Doctoral Student Prize

{"en"=>"Siyuan Guo wins 2024 MPI-IS Outstanding Female Doctoral Student Prize", "de"=>"Siyuan Guo gewinnt den MPI-IS Outstanding Female Doctoral Student Prize 2024 "}
Publication Empirical Inference 2024-07-01

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

Publication Empirical Inference 2024-07-01

Improving Neural Additive Models with Bayesian Principles

Publication Empirical Inference 2024-07-01

Geometry-Aware Instrumental Variable Regression

Publication Empirical Inference 2024-07-01

Diffusive Gibbs Sampling

Publication Empirical Inference 2024-07-01

Products, Abstractions and Inclusions of Causal Spaces

Publication Empirical Inference Learning and Dynamical Systems Robotics 2024-07-01

Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion

Publication Empirical Inference 2024-07-01

Robustness of Nonlinear Representation Learning

Publication Learning and Dynamical Systems Empirical Inference 2024-07-01

Deep Backtracking Counterfactuals for Causally Compliant Explanations

Publication Empirical Inference 2024-07-01

Probabilistic pathway-based multimodal factor analysis

Publication Perceiving Systems Empirical Inference 2024-05-01

Ghost on the Shell: An Expressive Representation of General 3D Shapes

Ghost on the Shell: An Expressive Representation of General {3D} Shapes
Publication Empirical Inference Perceiving Systems 2024-05-01

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization