Arash Mehrjou

According to our database, Arash Mehrjou authored at least 39 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases.

Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Samir Bhatt, Bernhard Schölkopf, Stefan Bauer

PLoS Comput. Biol., January, 2023

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data.

Mathieu Chevalley, Jacob Sackett-Sanders, Yusuf Roohani, Pascal Notin, Artemy Bakulin, Dariusz Brzezinski, Kaiwen Deng, Yuanfang Guan, Justin Hong, Michael Ibrahim, Wojciech Kotlowski, Marcin Kowiel, Panagiotis Misiakos, Achille Nazaret, Markus Püschel, Chris Wendler, Arash Mehrjou, Patrick Schwab

CoRR, 2023

Multi-omics Prediction from High-content Cellular Imaging with Deep Learning.

Rahil Mehrizi, Arash Mehrjou, Maryana Alegro, Yi Zhao, Benedetta Carbone, Carl Fishwick, Johanna Vappiani, Jing Bi, Siobhan Sanford, Hakan Keles, Marcus Bantscheff, Cuong Nguyen, Patrick Schwab

CoRR, 2023

Diffusion Based Representation Learning.

Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou

Proceedings of the International Conference on Machine Learning, 2023

DiscoBAX: Discovery of optimal intervention sets in genomic experiment design.

Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab

Proceedings of the International Conference on Machine Learning, 2023

2022

Diffusion Models for Video Prediction and Infilling.

Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

Trans. Mach. Learn. Res., 2022

FED-CD: Federated Causal Discovery from Interventional and Observational Data.

Amin Abyaneh, Nino Scherrer, Patrick Schwab, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou

CoRR, 2022

CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data.

Mathieu Chevalley, Yusuf Roohani, Arash Mehrjou, Jure Leskovec, Patrick Schwab

CoRR, 2022

From Points to Functions: Infinite-dimensional Representations in Diffusion Models.

Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou

CoRR, 2022

Federated Learning in Multi-Center Critical Care Research: A Systematic Case Study using the eICU Database.

Arash Mehrjou, Ashkan Soleymani, Annika Buchholz, Jürgen Hetzel, Patrick Schwab, Stefan Bauer

CoRR, 2022

Physical Derivatives: Computing policy gradients by physical forward-propagation.

Arash Mehrjou, Ashkan Soleymani, Stefan Bauer, Bernhard Schölkopf

CoRR, 2022

GeneDisco: A Benchmark for Experimental Design in Drug Discovery.

Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab

Proceedings of the Tenth International Conference on Learning Representations, 2022

GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL.

Sumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Dynamics of Learning and Learning of Dynamics.

Arash Mehrjou

PhD thesis, 2021

Federated Learning as a Mean-Field Game.

Arash Mehrjou

CoRR, 2021

Representation Learning in Continuous-Time Score-Based Generative Models.

Korbinian Abstreiter, Stefan Bauer, Arash Mehrjou

CoRR, 2021

Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases.

Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Bernhard Schölkopf, Stefan Bauer

CoRR, 2021

Neural Lyapunov Redesign.

Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning.

Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Real-time Prediction of COVID-19 related Mortality using Electronic Health Records.

Patrick Schwab, Arash Mehrjou, Sonali Parbhoo, Leo Anthony Celi, Jürgen Hetzel, Markus Hofer, Bernhard Schölkopf, Stefan Bauer

CoRR, 2020

Learning Dynamical Systems using Local Stability Priors.

Arash Mehrjou, Andrea Iannelli, Bernhard Schölkopf

CoRR, 2020

Artificial Buildings: Safety, Complexity and a Quantifiable Measure of Beauty.

Arash Mehrjou

CoRR, 2020

Automatic Policy Synthesis to Improve the Safety of Nonlinear Dynamical Systems.

Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf

CoRR, 2020

Dual Instrumental Variable Regression.

Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Counterfactuals uncover the modular structure of deep generative models.

Michel Besserve, Arash Mehrjou, Rémy Sun, Bernhard Schölkopf

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Dual IV: A Single Stage Instrumental Variable Regression.

Krikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj

CoRR, 2019

Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces.

Arash Mehrjou, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

CoRR, 2019

The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA.

Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Deep Nonlinear Non-Gaussian Filtering for Dynamical Systems.

Arash Mehrjou, Bernhard Schölkopf

CoRR, 2018

A Local Information Criterion for Dynamical Systems.

Arash Mehrjou, Friedrich Solowjow, Sebastian Trimpe, Bernhard Schölkopf

CoRR, 2018

Minimum Information Exchange in Distributed Systems.

Friedrich Solowjow, Arash Mehrjou, Bernhard Schölkopf, Sebastian Trimpe

CoRR, 2018

Distribution Aware Active Learning.

Arash Mehrjou, Mehran Khodabandeh, Greg Mori

CoRR, 2018

Deep Energy Estimator Networks.

Saeed Saremi, Arash Mehrjou, Bernhard Schölkopf, Aapo Hyvärinen

CoRR, 2018

Analysis of Nonautonomous Adversarial Systems.

Arash Mehrjou

CoRR, 2018

Tempered Adversarial Networks.

Mehdi S. M. Sajjadi, Giambattista Parascandolo, Arash Mehrjou, Bernhard Schölkopf

Proceedings of the 6th International Conference on Learning Representations, 2018

Fidelity-Weighted Learning.

Mostafa Dehghani, Arash Mehrjou, Stephan Gouws, Jaap Kamps, Bernhard Schölkopf

Proceedings of the 6th International Conference on Learning Representations, 2018

Efficient Encoding of Dynamical Systems Through Local Approximations.

Friedrich Solowjow, Arash Mehrjou, Bernhard Schölkopf, Sebastian Trimpe

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Annealed Generative Adversarial Networks.

Arash Mehrjou, Bernhard Schölkopf, Saeed Saremi

CoRR, 2017

2016

Improved Bayesian information criterion for mixture model selection.

Arash Mehrjou, Reshad Hosseini, Babak Nadjar Araabi

Pattern Recognit. Lett., 2016