Ehsan Hajiramezanali

According to our database, Ehsan Hajiramezanali authored at least 24 papers between 2018 and 2024.

Collaborative distances:

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

2024

MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction.

Carl Edwards, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Heng Ji, Gabriele Scalia

CoRR, 2024

Cell Morphology-Guided Small Molecule Generation with GFlowNets.

Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michal Koziarski

CoRR, 2024

Adding Conditional Control to Diffusion Models with Reinforcement Learning.

Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali

CoRR, 2024

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani

CoRR, 2024

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine

CoRR, 2024

Feedback Efficient Online Fine-Tuning of Diffusion Models.

Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Toward the Identifiability of Comparative Deep Generative Models.

Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev

Proceedings of the Causal Learning and Reasoning, 2024

Conformalized Deep Splines for Optimal and Efficient Prediction Sets.

Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction.

You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali

Proceedings of the Machine Learning in Computational Biology, November 30, 2023

Towards Understanding and Improving GFlowNet Training.

Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani

Proceedings of the International Conference on Machine Learning, 2023

2022

Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19.

Saleh Afroogh, Amir Esmalian, Ali Mostafavi, Ali Akbari, Kambiz Rasoulkhani, Shahriar Esmaeili, Ehsan Hajiramezanali

Ethics Inf. Technol., 2022

Conditional Diffusion with Less Explicit Guidance via Model Predictive Control.

Max W. Shen, Ehsan Hajiramezanali, Gabriele Scalia, Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Andreas Loukas

CoRR, 2022

Parameter Averaging for Robust Explainability.

Talip Ucar, Ehsan Hajiramezanali

CoRR, 2022

MoReL: Multi-omics Relational Learning.

Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Bayesian Graph Contrastive Learning.

Arman Hasanzadeh, Mohammadreza Armandpour, Ehsan Hajiramezanali, Mingyuan Zhou, Nick Duffield, Krishna Narayanan

CoRR, 2021

SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning.

Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

BayReL: Bayesian Relational Learning for Multi-omics Data Integration.

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian

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

Bayesian Graph Neural Networks with Adaptive Connection Sampling.

Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian

Proceedings of the 37th International Conference on Machine Learning, 2020

Semi-Implicit Stochastic Recurrent Neural Networks.

Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model.

Ehsan Hajiramezanali, Seyyed Hamed Fouladi, Hamidreza Amindavar

CoRR, 2019

Semi-Implicit Graph Variational Auto-Encoders.

Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Graph Recurrent Neural Networks.

Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data.

Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable Optimal Bayesian Classification of Single-Cell Trajectories under Regulatory Model Uncertainty.

Ehsan Hajiramezanali, Mahdi Imani, Ulisses M. Braga-Neto, Xiaoning Qian, Edward R. Dougherty

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018