Amirmohammad Rooshenas

According to our database, Amirmohammad Rooshenas authored at least 20 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Steered Generation via Gradient-Based Optimization on Sparse Query Features.

Sumanta Bhattacharyya, Pedram Rooshenas

CoRR, May, 2026

TARO: Temporal Adversarial Rectification Optimization Using Diffusion Models as Purifiers.

Daniel Wesego, Pedram Rooshenas

CoRR, May, 2026

2025

Audited Reasoning Refinement: Fine-Tuning Language Models via LLM-Guided Step-Wise Evaluation and Correction.

Sumanta Bhattacharyya, Sara Riazi, Pedram Rooshenas

CoRR, September, 2025

Steered Generation via Gradient Descent on Sparse Features.

Sumanta Bhattacharyya, Pedram Rooshenas

CoRR, February, 2025

LLM-Driven Feedback for Enhancing Conceptual Design Learning in Database Systems Courses.

Sara Riazi, Pedram Rooshenas

Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1, 2025

2024

Score-Based Multimodal Autoencoder.

Daniel Wesego, Pedram Rooshenas

Trans. Mach. Learn. Res., 2024

Revising Multimodal VAEs with Diffusion Decoders.

Daniel Wesego, Amirmohammad Rooshenas

CoRR, 2024

2023

Score-Based Multimodal Autoencoders.

Daniel Wesego, Amirmohammad Rooshenas

CoRR, 2023

Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography.

Akarsh Pokkunuru, Pedram Rooshenas, Thilo Strauss, Anuj Abhishek, Taufiquar Khan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models.

Sumanta Bhattacharyya, Amirmohammad Rooshenas, Subhajit Naskar, Simeng Sun, Mohit Iyyer, Andrew McCallum

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models.

Subhajit Naskar, Amirmohammad Rooshenas, Simeng Sun, Mohit Iyyer, Andrew McCallum

CoRR, 2020

Differential Equation Units: Learning Functional Forms of Activation Functions from Data.

MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions.

MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas

CoRR, 2019

Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks.

Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Training Structured Prediction Energy Networks with Indirect Supervision.

Amirmohammad Rooshenas, Aishwarya Kamath, Andrew McCallum

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2016

Discriminative Structure Learning of Arithmetic Circuits.

Amirmohammad Rooshenas, Daniel Lowd

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

The Libra toolkit for probabilistic models.

Daniel Lowd, Amirmohammad Rooshenas

J. Mach. Learn. Res., 2015

2014

Learning Sum-Product Networks with Direct and Indirect Variable Interactions.

Amirmohammad Rooshenas, Daniel Lowd

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Learning Markov Networks With Arithmetic Circuits.

Daniel Lowd, Amirmohammad Rooshenas

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

Learning Tractable Graphical Models Using Mixture of Arithmetic Circuits.

Amirmohammad Rooshenas, Daniel Lowd

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013