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2020 – today
- 2024
[c6]Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause:
Adversarial Causal Bayesian Optimization. ICLR 2024- [i6]Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause:
Standardizing Structural Causal Models. CoRR abs/2406.11601 (2024) - 2023
- [c5]Scott Sussex, Anastasia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. ICLR 2023 - [i5]Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. CoRR abs/2307.16625 (2023) - 2022
- [c4]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. NeurIPS 2022 - [c3]Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M. Buhmann, Andreas Krause:
Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS 2022 - [i4]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. CoRR abs/2205.12934 (2022) - [i3]Scott Sussex, Anastasiia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. CoRR abs/2211.10257 (2022) - 2021
- [c2]Scott Sussex, Caroline Uhler, Andreas Krause:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NeurIPS 2021: 777-788 - [i2]Scott Sussex, Andreas Krause, Caroline Uhler:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. CoRR abs/2105.14024 (2021)
2010 – 2019
- 2019
- [c1]Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez:
Combining parametric and nonparametric models for off-policy evaluation. ICML 2019: 2366-2375 - [i1]Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez:
Combining Parametric and Nonparametric Models for Off-Policy Evaluation. CoRR abs/1905.05787 (2019)
Coauthor Index
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