Ehsan Hajiramezanali

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 34

Top Topics

Diffusion Models

Predictive Control

Top Venues

Publications

Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali
Adding Conditional Control to Diffusion Models with Reinforcement Learning. CoRR (2024)
Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev
Toward the Identifiability of Comparative Deep Generative Models. CoRR (2024)
Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia
Conformalized Deep Splines for Optimal and Efficient Prediction Sets. AISTATS (2024)
Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Tommaso Biancalani, Sergey Levine
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control. CoRR (2024)
Masatoshi Uehara, Yulai Zhao, Kevin Black, Ehsan Hajiramezanali, Gabriele Scalia, Nathaniel Lee Diamant, Alex M. Tseng, Sergey Levine, Tommaso Biancalani
Feedback Efficient Online Fine-Tuning of Diffusion Models. CoRR (2024)
Masatoshi Uehara, Yulai Zhao, Ehsan Hajiramezanali, Gabriele Scalia, Gökcen Eraslan, Avantika Lal, Sergey Levine, Tommaso Biancalani
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. CoRR (2024)
Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev
Toward the Identifiability of Comparative Deep Generative Models. CLeaR (2024)
Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani
Towards Understanding and Improving GFlowNet Training. CoRR (2023)
Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani
Towards Understanding and Improving GFlowNet Training. ICML (2023)
You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali
Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. MLCB (2023)
Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia
Conformalized Deep Splines for Optimal and Efficient Prediction Sets. CoRR (2023)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian
MoReL: Multi-omics Relational Learning. CoRR (2022)
Talip Ucar, Ehsan Hajiramezanali
Parameter Averaging for Robust Explainability. CoRR (2022)
Max W. Shen, Ehsan Hajiramezanali, Gabriele Scalia, Alex Tseng, Nathaniel Diamant, Tommaso Biancalani, Andreas Loukas
Conditional Diffusion with Less Explicit Guidance via Model Predictive Control. CoRR (2022)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian
MoReL: Multi-omics Relational Learning. ICLR (2022)
Saleh Afroogh, Amir Esmalian, Ali Mostafavi, Ali Akbari, Kambiz Rasoulkhani, Shahriar Esmaeili, Ehsan Hajiramezanali
Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19. Ethics Inf. Technol. 24 (3) (2022)
Arman Hasanzadeh, Mohammadreza Armandpour, Ehsan Hajiramezanali, Mingyuan Zhou, Nick Duffield, Krishna Narayanan
Bayesian Graph Contrastive Learning. CoRR (2021)
Saleh Afroogh, Amir Esmalian, Ali Mostafavi, Ali Akbari, Kambiz Rasoulkhani, Shahriar Esmaeili, Ehsan Hajiramezanali
Tracing app technology: An ethical review in the COVID-19 era and directions for post-COVID-19. CoRR (2021)
Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. CoRR (2021)
Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. NeurIPS (2021)
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML (2020)
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. NeurIPS (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Xiaoning Qian
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. CoRR (2020)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Graph Variational Auto-Encoders. CoRR (2019)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian
Variational Graph Recurrent Neural Networks. CoRR (2019)
Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian
Variational Graph Recurrent Neural Networks. NeurIPS (2019)
Ehsan Hajiramezanali, Seyyed Hamed Fouladi, Hamidreza Amindavar
A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model. CoRR (2019)
Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS (2019)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Stochastic Recurrent Neural Networks. CoRR (2019)
Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. NeurIPS (2018)
Ehsan Hajiramezanali, Mahdi Imani, Ulisses M. Braga-Neto, Xiaoning Qian, Edward R. Dougherty
Scalable Optimal Bayesian Classification of Single-Cell Trajectories under Regulatory Model Uncertainty. BCB (2018)
Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data. CoRR (2018)