Tolooshams, Bahareh

10 publications

CVPR 2025 A Unified Model for Compressed Sensing MRI Across Undersampling Patterns Armeet Singh Jatyani, Jiayun Wang, Aditi Chandrashekar, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar

ICLR 2025 Diffusion State-Guided Projected Gradient for Inverse Problems Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar

NeurIPS 2025 From Flat to Hierarchical: Extracting Sparse Representations with Matching Pursuit Valérie Costa, Thomas Fel, Ekdeep Singh Lubana, Bahareh Tolooshams, Demba E. Ba

NeurIPS 2025 NOBLE - Neural Operator with Biologically-Informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams, Philip H. Wong, Costas A. Anastassiou, Anima Anandkumar

TMLR 2024 Discriminative Reconstruction via Simultaneous Dense and Sparse Coding Abiy Tasissa, Manos Theodosis, Bahareh Tolooshams, Demba E. Ba

NeurIPSW 2024 Projected Low-Rank Gradient in Diffusion-Based Models for Inverse Problems Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar

NeurIPSW 2024 Unifying Subsampling Pattern Variations for Compressed Sensing MRI with Neural Operators Armeet Singh Jatyani, Jiayun Wang, Zihui Wu, Miguel Liu-Schiaffini, Bahareh Tolooshams, Anima Anandkumar

ICML 2023 Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models Alexander Lin, Bahareh Tolooshams, Yves Atchade, Demba E. Ba

TMLR 2022 Stable and Interpretable Unrolled Dictionary Learning Bahareh Tolooshams, Demba E. Ba

ICML 2020 Convolutional Dictionary Learning Based Auto-Encoders for Natural Exponential-Family Distributions Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba