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ORCIDEhsan Hajiramezanali
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2020 – today
- 2024
[c14]Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia:
Conformalized Deep Splines for Optimal and Efficient Prediction Sets. AISTATS 2024: 1657-1665- [c13]Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev:
Toward the Identifiability of Comparative Deep Generative Models. CLeaR 2024: 868-912 - [c12]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. ICML 2024 - [i21]Romain Lopez, Jan-Christian Hütter, Ehsan Hajiramezanali, Jonathan K. Pritchard, Aviv Regev:
Toward the Identifiability of Comparative Deep Generative Models. CoRR abs/2401.15903 (2024) - [i20]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 abs/2402.15194 (2024) - [i19]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 abs/2402.16359 (2024) - [i18]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 abs/2405.19673 (2024) - [i17]Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali:
Adding Conditional Control to Diffusion Models with Reinforcement Learning. CoRR abs/2406.12120 (2024) - [i16]Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michal Koziarski:
Cell Morphology-Guided Small Molecule Generation with GFlowNets. CoRR abs/2408.05196 (2024) - 2023
- [c11]Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani:
Towards Understanding and Improving GFlowNet Training. ICML 2023: 30956-30975 - [c10]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: 10-22 - [i15]Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani:
Towards Understanding and Improving GFlowNet Training. CoRR abs/2305.07170 (2023) - [i14]Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia:
Conformalized Deep Splines for Optimal and Efficient Prediction Sets. CoRR abs/2311.00774 (2023) - 2022
- [j1]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): 30 (2022) - [c9]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. ICLR 2022 - [i13]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. CoRR abs/2203.08149 (2022) - [i12]Talip Ucar, Ehsan Hajiramezanali:
Parameter Averaging for Robust Explainability. CoRR abs/2208.03249 (2022) - [i11]Max W. Shen, Ehsan Hajiramezanali, Gabriele Scalia, Alex M. Tseng, Nathaniel Diamant, Tommaso Biancalani, Andreas Loukas:
Conditional Diffusion with Less Explicit Guidance via Model Predictive Control. CoRR abs/2210.12192 (2022) - 2021
- [c8]Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards:
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. NeurIPS 2021: 18853-18865 - [i10]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 abs/2108.12673 (2021) - [i9]Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards:
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. CoRR abs/2110.04361 (2021) - [i8]Arman Hasanzadeh, Mohammadreza Armandpour, Ehsan Hajiramezanali, Mingyuan Zhou, Nick Duffield, Krishna Narayanan:
Bayesian Graph Contrastive Learning. CoRR abs/2112.07823 (2021) - 2020
- [c7]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP 2020: 3342-3346 - [c6]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML 2020: 4094-4104 - [c5]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. NeurIPS 2020 - [i7]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR abs/2006.04064 (2020) - [i6]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. CoRR abs/2010.05895 (2020)
2010 – 2019
- 2019
- [c4]Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. NeurIPS 2019: 10700-10710 - [c3]Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS 2019: 10711-10722 - [i5]Ehsan Hajiramezanali, Seyyed Hamed Fouladi, Hamidreza Amindavar:
A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model. CoRR abs/1902.04671 (2019) - [i4]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. CoRR abs/1908.07078 (2019) - [i3]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. CoRR abs/1908.09710 (2019) - [i2]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. CoRR abs/1910.12819 (2019) - 2018
- [c2]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: 596-597 - [c1]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: 9133-9142 - [i1]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 abs/1810.09433 (2018)
Coauthor Index
aka: Nick Duffield
aka: Krishna R. Narayanan
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