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 (BCB, 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 (NeurIPS, 2018)

Variational Graph Recurrent Neural Networks. - Ehsan Hajiramezanali; Arman Hasanzadeh; Krishna R. Narayanan; Nick Duffield; Mingyuan Zhou; Xiaoning Qian (NeurIPS, 2019)

Semi-Implicit Graph Variational Auto-Encoders. - Arman Hasanzadeh; Ehsan Hajiramezanali; Krishna R. Narayanan; Nick Duffield; Mingyuan Zhou; Xiaoning Qian (NeurIPS, 2019)

A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model. - Ehsan Hajiramezanali; Seyyed Hamed Fouladi; Hamidreza Amindavar (CoRR, 2019)

Semi-Implicit Stochastic Recurrent Neural Networks. - Ehsan Hajiramezanali; Arman Hasanzadeh; Nick Duffield; Krishna Narayanan 001; Mingyuan Zhou; Xiaoning Qian (ICASSP, 2020)

Bayesian Graph Neural Networks with Adaptive Connection Sampling. - Arman Hasanzadeh; Ehsan Hajiramezanali; Shahin Boluki; Mingyuan Zhou; Nick Duffield; Krishna Narayanan 001; Xiaoning Qian (ICML, 2020)

BayReL: Bayesian Relational Learning for Multi-omics Data Integration. - Ehsan Hajiramezanali; Arman Hasanzadeh; Nick Duffield; Krishna Narayanan 001; Xiaoning Qian (NeurIPS, 2020)

SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning. - Talip Ucar; Ehsan Hajiramezanali; Lindsay Edwards (NeurIPS, 2021)

Bayesian Graph Contrastive Learning. - Arman Hasanzadeh; Mohammadreza Armandpour; Ehsan Hajiramezanali; Mingyuan Zhou; Nick Duffield; Krishna Narayanan 001 (CoRR, 2021)

MoReL: Multi-omics Relational Learning. - Arman Hasanzadeh; Ehsan Hajiramezanali; Nick Duffield; Xiaoning Qian (ICLR, 2022)

Parameter Averaging for Robust Explainability. - Talip Ucar; Ehsan Hajiramezanali (CoRR, 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)

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)

Towards Understanding and Improving GFlowNet Training. - Max W. Shen; Emmanuel Bengio; Ehsan Hajiramezanali; Andreas Loukas; Kyunghyun Cho; Tommaso Biancalani (ICML, 2023)

Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. - You Wu; Omid Bazgir; Yongju Lee; Tommaso Biancalani; James Lu; Ehsan Hajiramezanali (MLCB, 2023)

Conformalized Deep Splines for Optimal and Efficient Prediction Sets. - Nathaniel Diamant; Ehsan Hajiramezanali; Tommaso Biancalani; Gabriele Scalia (AISTATS, 2024)

Toward the Identifiability of Comparative Deep Generative Models. - Romain Lopez; Jan-Christian Hütter; Ehsan Hajiramezanali; Jonathan K. Pritchard; Aviv Regev (CLeaR, 2024)

Feedback Efficient Online Fine-Tuning of Diffusion Models. - Masatoshi Uehara; Yulai Zhao 002; Kevin Black; Ehsan Hajiramezanali; Gabriele Scalia; Nathaniel Lee Diamant; Alex M. Tseng; Sergey Levine; Tommaso Biancalani (ICML, 2024)

GFlowNet Assisted Biological Sequence Editing. - Pouya M. Ghari; Alex M. Tseng; Gökcen Eraslan; Romain Lopez; Tommaso Biancalani; Gabriele Scalia; Ehsan Hajiramezanali (NeurIPS, 2024)

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. - Masatoshi Uehara; Yulai Zhao 002; Ehsan Hajiramezanali; Gabriele Scalia; Gökcen Eraslan; Avantika Lal; Sergey Levine; Tommaso Biancalani (NeurIPS, 2024)

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control. - Masatoshi Uehara; Yulai Zhao 002; Kevin Black; Ehsan Hajiramezanali; Gabriele Scalia; Nathaniel Lee Diamant; Alex M. Tseng; Tommaso Biancalani; Sergey Levine (CoRR, 2024)

Adding Conditional Control to Diffusion Models with Reinforcement Learning. - Yulai Zhao 002; Masatoshi Uehara; Gabriele Scalia; Tommaso Biancalani; Sergey Levine; Ehsan Hajiramezanali (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)

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)

Score-based Explainability for Graph Representations. - Ehsan Hajiramezanali; Sepideh Maleki; Max W. Shen; Kangway V. Chuang; Tommaso Biancalani; Gabriele Scalia (Trans. Mach. Learn. Res., 2024)

Adding Conditional Control to Diffusion Models with Reinforcement Learning. - Yulai Zhao 002; Masatoshi Uehara; Gabriele Scalia; Sun-Yuan Kung; Tommaso Biancalani; Sergey Levine; Ehsan Hajiramezanali (ICLR, 2025)

RAG-Enhanced Collaborative LLM Agents for Drug Discovery. - Namkyeong Lee; Edward De Brouwer; Ehsan Hajiramezanali; Chanyoung Park 001; Gabriele Scalia (CoRR, 2025)

Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design. - Xingyu Su; Xiner Li; Masatoshi Uehara; Sunwoo Kim; Yulai Zhao 002; Gabriele Scalia; Ehsan Hajiramezanali; Tommaso Biancalani; Degui Zhi; Shuiwang Ji (CoRR, 2025)