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Jonas Peters

20 papers · 2008–2025 · 6 conferences · across top CS/AI conferences

Achievements

๐Ÿƒ Academic Marathon (17) ๐ŸŒ‰ Interdisciplinary Bridge ๐Ÿ—บ๏ธ Taxonomy Completionist (24) ๐ŸŒˆ Renaissance Researcher (6) ๐Ÿงญ Keyword Pioneer ๐Ÿฃ Hot Topic Early Bird ๐Ÿ Cross-Pollinator (12) ๐ŸŒ Conference Polyglot (6) ๐ŸŒŸ Keyword Trendsetter Combo (3) ๐Ÿ† Keyword Champion ๐Ÿ”ฌ Deep Specialist (17) ๐Ÿ’Ž Century Club (20) ๐Ÿ“ˆ Trend Setter ๐Ÿ—ƒ๏ธ Keyword Collector (77) ๐Ÿš€ Conference Pioneer

Conferences

JMLR (9) ICML (5) NIPS (3) AISTATS (1) ICLR (1) UAI (1)

Top co-authors

Bernhard Schรถlkopf (8) Dominik Janzing (6) Niklas Pfister (5) Nikolaj Thams (3) Joris M. Mooij (3) Sorawit Saengkyongam (3) Patrik O. Hoyer (1) Rikke Sรธndergaard (1) Joaquin Quiรฑonero-Candela (1) Susan Murphy (1)

Keywords

causal inference (12) causal discovery (9) additive noise model (6) time series (3) latent variable (3) domain generalization (3) structural equation model (3) instrumental variable (3) invariant prediction (2) linear model (2) graphical model (2) directed acyclic graph (2) covariate shift (1) asymptotic analysis (1) granger causality (1) online learning (1) matrix decomposition (1) time series causal discovery (1) graph theory (1) zero-shot learning (1)

Papers

Invariant Subspace Decomposition JMLR 2025
Identifying Representations for Intervention Extrapolation ICLR 2024
Effect-Invariant Mechanisms for Policy Generalization JMLR 2024
Identifying Causal E๏ฌ€ects using Instrumental Time Series: Nuisance IV and Correcting for the Past JMLR 2024
Structure Learning for Directed Trees JMLR 2022
Identifiability of sparse causal effects using instrumental variables UAI 2022
Invariant Ancestry Search ICML 2022
Exploiting Independent Instruments: Identification and Distribution Generalization ICML 2022
Regularizing towards Causal Invariance: Linear Models with Proxies ICML 2021
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables JMLR 2020
Invariant Models for Causal Transfer Learning JMLR 2018
Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks JMLR 2016
The Arrow of Time in Multivariate Time Series ICML 2016
Removing systematic errors for exoplanet search via latent causes ICML 2015
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions NIPS 2015
Causal Discovery with Continuous Additive Noise Models JMLR 2014
Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising JMLR 2013
Causal Inference on Time Series using Restricted Structural Equation Models NIPS 2013
Identifying Cause and Effect on Discrete Data using Additive Noise Models AISTATS 2010
Nonlinear causal discovery with additive noise models NIPS 2008