Workshop
Learning-Based Solutions for Inverse Problems
Shirin Jalali · Chris Metzler · Ajil Jalal · Jon Tamir · Reinhard Heckel · Paul Hand · Arian Maleki · Richard Baraniuk
Room 214
Sat 16 Dec, 7 a.m. PST
Inverse problems are ubiquitous in science, medicine, and engineering,and research in this area has produced real-world impact in medical tomography, seismic imaging, computational photography, and other domains. The recent rapid progress in learning-based image generation raises exciting opportunities in inverse problems, and this workshop seeks to gather a diverse set of participants who apply machine learning to inverse problems, from mathematicians and computer scientists to physicists and biologists. This gathering will facilitate new collaborations and will help develop more effective, reliable, and trustworthy learning-based solutions to inverse problems.
Schedule
Sat 7:00 a.m. - 7:30 a.m.
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Invited Talk by Namrata Vaswani
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Invited Talk
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SlidesLive Video |
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Sat 7:30 a.m. - 8:00 a.m.
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Invited Talk by Stella Yu
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Invited Talk
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SlidesLive Video |
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Sat 8:00 a.m. - 8:30 a.m.
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Break
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Sat 8:30 a.m. - 8:45 a.m.
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Phase Retrieval via Deep Expectation-Consistent Approximation
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Oral
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SlidesLive Video |
Saurav Shastri · Philip Schniter 🔗 |
Sat 8:45 a.m. - 9:00 a.m.
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Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
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Oral
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SlidesLive Video |
Gabriele Corso · Yilun Xu · Valentin De Bortoli · Regina Barzilay · Tommi Jaakkola 🔗 |
Sat 9:00 a.m. - 9:30 a.m.
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Invited Talk by Jong Chul Ye: "Regularization by Texts for Latent Diffusion Inverse Solvers"
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Invited Talk
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SlidesLive Video |
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Sat 9:30 a.m. - 10:00 a.m.
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Invited Talk by Ben Poole: "Diffusion Priors for 3D Reconstruction"
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Invited Talk
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Sat 10:00 a.m. - 11:30 a.m.
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Lunch Break
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Sat 11:30 a.m. - 11:45 a.m.
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Space-Time Implicit Neural Representations for Atomic Electron Tomography on Dynamic Samples
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Oral
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SlidesLive Video |
Tiffany Chien · Colin Ophus · Laura Waller 🔗 |
Sat 11:45 a.m. - 12:00 p.m.
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AmbientFlow: Invertible generative models from incomplete, noisy imaging measurements
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Oral
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SlidesLive Video |
Varun Kelkar · Rucha Deshpande · Arindam Banerjee · Mark Anastasio 🔗 |
Sat 12:00 p.m. - 1:00 p.m.
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Poster Session
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Poster Session
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Sat 1:00 p.m. - 1:30 p.m.
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Invited Talk by Eric Price
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Invited Talk
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SlidesLive Video |
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Sat 1:30 p.m. - 2:00 p.m.
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Break
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Sat 2:00 p.m. - 2:30 p.m.
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Invited Talk by Ellen Zhong
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Invited Talk
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SlidesLive Video |
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Sat 2:30 p.m. - 2:45 p.m.
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Quantifying Generative Model Uncertainty in Posterior Sampling Methods for Computational Imaging
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Oral
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SlidesLive Video |
Canberk Ekmekci · Mujdat Cetin 🔗 |
Sat 2:45 p.m. - 3:00 p.m.
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Model-adapted Fourier sampling for generative compressed sensing
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Oral
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SlidesLive Video |
Aaron Berk · Simone Brugiapaglia · Yaniv Plan · Matthew Scott · Xia Sheng · Ozgur Yilmaz 🔗 |
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Provably Convergent Data-Driven Convex-Nonconvex Regularization ( Poster ) > link | Zakhar Shumaylov · Jeremy Budd · Subhadip Mukherjee · Carola-Bibiane Schönlieb 🔗 |
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SUD$^2$: Supervision by Denoising Diffusion Models for Image Reconstruction ( Poster ) > link | Matthew Chan · Sean Young · Chris Metzler 🔗 |
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Feature Importance Random Search for Hyperparameter Optimization of Data-Consistent Model Inversion ( Poster ) > link | Isaiah Onando Mulang' · Stephen Obonyo · Timothy Rumbell · Viatcheslav Gurev · Wanjiru Catherine 🔗 |
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Boosting Weakly Convex Ridge Regularizers with Spatial Adaptivity ( Poster ) > link | Sebastian Neumayer · Mehrsa Pourya · Alexis Goujon · Michael Unser 🔗 |
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Solving Inverse Problems with Ambient Diffusion ( Poster ) > link | Giannis Daras · Alex Dimakis 🔗 |
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Efficient Bayesian Computational Imaging with a Surrogate Score-Based Prior ( Poster ) > link | Berthy Feng · Katherine Bouman 🔗 |
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Poisson-Gaussian Holographic Phase Retrieval with Score-based Image Prior ( Poster ) > link | Jason Hu · Zongyu Li · Xiaojian Xu · Liyue Shen · Jeff A Fessler 🔗 |
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Volume-Oriented Uncertainty for Inverse Problems ( Poster ) > link | Omer Belhasin · Yaniv Romano · Daniel Freedman · Ehud Rivlin · Michael Elad 🔗 |
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Score-Based Likelihood Characterization for Inverse Problems in the Presence of Non-Gaussian Noise ( Poster ) > link | Ronan Legin · Alexandre Adam · Yashar Hezaveh · Laurence Perreault-Levasseur 🔗 |
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Improved Black-box Variational Inference for High-dimensional Bayesian Inversion involving Black-box Simulators ( Poster ) > link | Dhruv Patel · Jonghyun Lee · Matthew Farthing · Tyler Hesser · Peter Kitanidis · Eric Darve 🔗 |
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Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models ( Poster ) > link | Zalan Fabian · Berk Tinaz · Mahdi Soltanolkotabi 🔗 |
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Self-supervised Low-rank plus Sparse Network for Radial MRI Reconstruction ( Poster ) > link | Andrei Mancu · Wenqi Huang · Gastao da Cruz · Daniel Rueckert · Kerstin Hammernik 🔗 |
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OptoGPT: A Versatile Inverse Design Model for Optical Multilayer Thin Film Structures ( Poster ) > link | Taigao Ma · L. Jay Guo · Haozhu Wang 🔗 |
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nbi: the Astronomer's Package for Neural Posterior Estimation ( Poster ) > link | Keming Zhang · Joshua Bloom · Nina Hernitschek 🔗 |
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Conditional score-based generative models for solving physics-based inverse problems ( Poster ) > link | Agnimitra Dasgupta · Javier Murgoitio Esandi · Deep Ray · Assad Oberai 🔗 |
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Inferring Cardiovascular Biomarkers with Hybrid Model Learning ( Poster ) > link | Ortal Senouf · Jens Behrmann · Joern-Henrik Jacobsen · Pascal Frossard · Emmanuel Abbe · Antoine Wehenkel 🔗 |
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Switching policies for solving inverse problems ( Poster ) > link | Tim Bakker · Fabio Valerio Massoli · Thomas Hehn · Tribhuvanesh Orekondy · Arash Behboodi 🔗 |
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Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models ( Poster ) > link | Sriram Ravula · Brett Levac · Ajil Jalal · Jon Tamir · Alex Dimakis 🔗 |
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Regularization by Denoising Diffusion Process for MRI Reconstruction ( Poster ) > link | Batu Ozturkler · Morteza Mardani · Arash Vahdat · Jan Kautz · John Pauly 🔗 |
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Blind Image Deblurring with Unknown Kernel Size and Substantial Noise ( Poster ) > link | Zhong Zhuang · Taihui Li · Hengkang Wang · Ju Sun 🔗 |
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What’s in a Prior? Learned Proximal Networks for Inverse Problems ( Poster ) > link | Zhenghan Fang · Sam Buchanan · Jeremias Sulam 🔗 |
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Multilook compressive sensing in the presence of speckle noise ( Poster ) > link | Xi Chen · Zhewen Hou · Chris Metzler · Arian Maleki · Shirin Jalali 🔗 |
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How Good Are Deep Generative Models for Solving Inverse Problems? ( Poster ) > link | Shichong Peng · Alireza Moazeni · Ke Li 🔗 |
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Variational Diffusion Models for MRI Blind Inverse Problems ( Poster ) > link | Julio Oscanoa · Cagan Alkan · Daniel Abraham · Aizada Nurdinova · Daniel Ennis · Shreyas Vasanawala · Morteza Mardani · John Pauly 🔗 |
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Mask-Agnostic Posterior Sampling MRI via Conditional GANs with Guided Reconstruction ( Poster ) > link | Matthew Bendel · Rizwan Ahmad · Philip Schniter 🔗 |
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Using Deep Feature Distances for Evaluating MR Image Reconstruction Quality ( Poster ) > link |
12 presentersPhilip M. Adamson · Arjun Desai · Jeffrey Dominic · Christian Bluethgen · Jeff Wood · Ali Syed · Robert Boutin · Kathryn Stevens · Shreyas Vasanawala · John Pauly · Akshay Chaudhari · Beliz Gunel |
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Physics-guided Training of Neural Electromagnetic Wave Simulators with Time-reversal Consistency ( Poster ) > link | Charles Dove · Jatearoon Boondicharern · Laura Waller 🔗 |
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Multimodal Neural Surface Reconstruction: Recovering the Geometry and Appearance of 3D Scenes from Events and Grayscale Images ( Poster ) > link | Sazan Mahbub · Brandon Feng · Chris Metzler 🔗 |
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Phase Retrieval Using Double Deep Image Priors ( Poster ) > link | Zhong Zhuang · David Yang · David Barmherzig · Ju Sun 🔗 |
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Sequential data-consistent model inversion ( Poster ) > link | Timothy Rumbell · Wanjiru Catherine · Isaiah Onando Mulang' · Stephen Obonyo · James Kozloski · Viatcheslav Gurev 🔗 |
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Transformers Can Learn To Solve Linear-Inverse Problems In-Context ( Poster ) > link | Kabir Ahuja · Madhur Panwar · Navin Goyal 🔗 |
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Modeling GAN Latent Dynamics using Neural ODEs ( Poster ) > link | Weihao Xia · Yujiu Yang · Jing-Hao Xue 🔗 |
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Refined Tensorial Radiance Field: Harnessing Coordinate-Based Networks for Novel View Synthesis from Sparse Inputs ( Poster ) > link | Mingyu Kim · Kim Jun-Seong · Se-Young Yun · Jin-Hwa Kim 🔗 |