Ehsan Hajiramezanali
15 papers · 2018–2026 · 6 venues · across top CS/AI venues
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Core Methods
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Bayesian & Probabilistic
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Healthcare & Medicine
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Natural Language Processing
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Reinforcement Learning
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Keywords
diffusion model
(3)
reinforcement learning
(3)
reward function
(3)
representation learning
(3)
bayesian learning
(2)
multi-omics data
(2)
semi-implicit variational inference
(2)
generative model
(2)
bayesian inference
(2)
graph neural network
(2)
generative flow network
(2)
self-supervised learning
(1)
optimal transport
(1)
graph representation learning
(1)
uncertainty quantification
(1)
variational inference
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relational learning
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conformal prediction
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hierarchical model
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adaptive sampling
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Papers
RAG-Enhanced Collaborative LLM Agents for Drug Discovery
AAAI 2026
Adding Conditional Control to Diffusion Models with Reinforcement Learning
ICLR 2025
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models
NeurIPS 2024
Conformalized Deep Splines for Optimal and Efficient Prediction Sets
AISTATS 2024
Feedback Efficient Online Fine-Tuning of Diffusion Models
ICML 2024
GFlowNet Assisted Biological Sequence Editing
NeurIPS 2024
Toward the Identifiability of Comparative Deep Generative Models
CLeaR 2024
Towards Understanding and Improving GFlowNet Training
ICML 2023
MoReL: Multi-omics Relational Learning
ICLR 2022
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
NeurIPS 2021
Bayesian Graph Neural Networks with Adaptive Connection Sampling
ICML 2020
BayReL: Bayesian Relational Learning for Multi-omics Data Integration
NeurIPS 2020
Semi-Implicit Graph Variational Auto-Encoders
NeurIPS 2019
Variational Graph Recurrent Neural Networks
NeurIPS 2019
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data
NeurIPS 2018