Ehsan Hajiramezanali

According to our database1, Ehsan Hajiramezanali authored at least 19 papers between 2018 and 2024.

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Bibliography

2024
Feedback Efficient Online Fine-Tuning of Diffusion Models.
CoRR, 2024

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.
CoRR, 2024

Toward the Identifiability of Comparative Deep Generative Models.
CoRR, 2024

2023
Conformalized Deep Splines for Optimal and Efficient Prediction Sets.
CoRR, 2023

Towards Understanding and Improving GFlowNet Training.
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.
Ethics Inf. Technol., 2022

Conditional Diffusion with Less Explicit Guidance via Model Predictive Control.
CoRR, 2022

Parameter Averaging for Robust Explainability.
CoRR, 2022

MoReL: Multi-omics Relational Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Bayesian Graph Contrastive Learning.
CoRR, 2021

SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning.
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.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

Semi-Implicit Stochastic Recurrent Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model.
CoRR, 2019

Semi-Implicit Graph Variational Auto-Encoders.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Graph Recurrent Neural Networks.
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.
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.
Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018


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