Jonas Peters
20 papers · 2008–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (17)
🐣
Hot Topic Early Bird
🐝
Cross-Pollinator
(12)
🌍
Conference Polyglot
(6)
🌟
Keyword Trendsetter Combo
(3)
🏆
Keyword Champion
🔬
Deep Specialist
(17)
💎
Century Club
(20)
📈
Trend Setter
🗃️
Keyword Collector
(77)
🚀
Conference Pioneer
Conferences
JMLR (9)
ICML (5)
NIPS (3)
AISTATS (1)
ICLR (1)
UAI (1)
Top co-authors
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 Effects 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