Fast and accurate estimation of principal curvatures and directions for morphable models. - Justin Solomon 001 (SIGGRAPH Posters, 2007)

SIGGRAPH 2006: exploring the art and science of computer graphics. - Justin Solomon 001 (ACM Crossroads, 2007)

The science of shape: revolutionizing graphics and vision with the third dimension. - Justin Solomon 001 (ACM Crossroads, 2007)

Putting the science into computer science: treating introductory computer science as the study of algorithms. - Justin Solomon 001 (ACM SIGCSE Bull., 2007)

Introduction. - Justin Solomon 001 (ACM Crossroads, 2008)

Introduction: maxed out? - Justin Solomon 001 (ACM Crossroads, 2009)

Programmers, Professors, and Parasites: Credit and Co-Authorship in Computer Science. - Justin Solomon 001 (Sci. Eng. Ethics, 2009)

On Discrete Killing Vector Fields and Patterns on Surfaces. - Mirela Ben-Chen; Adrian Butscher; Justin Solomon 001; Leonidas J. Guibas (Comput. Graph. Forum, 2010)

Smoothed local histogram filters. - Michael Kass; Justin Solomon 001 (ACM Trans. Graph., 2010)

Discovery of Intrinsic Primitives on Triangle Meshes. - Justin Solomon 001; Mirela Ben-Chen; Adrian Butscher; Leonidas J. Guibas (Comput. Graph. Forum, 2011)

As-Killing-As-Possible Vector Fields for Planar Deformation. - Justin Solomon 001; Mirela Ben-Chen; Adrian Butscher; Leonidas J. Guibas (Comput. Graph. Forum, 2011)

Fast smoothed shock filtering. - Antoine Vacavant; Adelaide Albouy-Kissi; Pierre-Yves Menguy; Justin Solomon 001 (ICPR, 2012)

Soft Maps Between Surfaces. - Justin Solomon 001; Andy Nguyen; Adrian Butscher; Mirela Ben-Chen; Leonidas J. Guibas (Comput. Graph. Forum, 2012)

Flexible Developable Surfaces. - Justin Solomon 001; Etienne Vouga; Max Wardetzky; Eitan Grinspun (Comput. Graph. Forum, 2012)

Functional maps: a flexible representation of maps between shapes. - Maks Ovsjanikov; Mirela Ben-Chen; Justin Solomon 001; Adrian Butscher; Leonidas J. Guibas (ACM Trans. Graph., 2012)

Dirichlet Energy for Analysis and Synthesis of Soft Maps. - Justin Solomon 001; Leonidas J. Guibas; Adrian Butscher (Comput. Graph. Forum, 2013)

Wasserstein Propagation for Semi-Supervised Learning. - Justin Solomon 001; Raif M. Rustamov; Leonidas J. Guibas; Adrian Butscher (ICML, 2014)

A General Framework for Bilateral and Mean Shift Filtering. - Justin Solomon 001; Keenan Crane; Adrian Butscher; Chris Wojtan (CoRR, 2014)

Earth mover's distances on discrete surfaces. - Justin Solomon 001; Raif M. Rustamov; Leonidas J. Guibas; Adrian Butscher (ACM Trans. Graph., 2014)

Codimensional surface tension flow on simplicial complexes. - Bo Zhu 002; Ed Quigley; Matthew Cong; Justin Solomon 001; Ronald Fedkiw (ACM Trans. Graph., 2014)

Numerical Algorithms - Methods for Computer Vision, Machine Learning, and Graphics. - Justin Solomon 001 (CRC Press, 2015)

Exponential Integration for Hamiltonian Monte Carlo. - Wei-Lun Chao; Justin Solomon 001; Dominik L. Michels; Fei Sha (ICML, 2015)

PDE Approaches to Graph Analysis. - Justin Solomon 001 (CoRR, 2015)

Convolutional wasserstein distances: efficient optimal transportation on geometric domains. - Justin Solomon 001; Fernando de Goes; Gabriel Peyré; Marco Cuturi; Adrian Butscher; Andy Nguyen; Tao Du; Leonidas J. Guibas (ACM Trans. Graph., 2015)

Transportation techniques for geometric data processing. - Justin Solomon 001 (2015)

Gromov-Wasserstein Averaging of Kernel and Distance Matrices. - Gabriel Peyré; Marco Cuturi; Justin Solomon 001 (ICML, 2016)

Near-Isometric Level Set Tracking. - Michael Tao 001; Justin Solomon 001; Adrian Butscher (Comput. Graph. Forum, 2016)

Quantum Optimal Transport for Tensor Field Processing. - Gabriel Peyré; Lenaïc Chizat; François-Xavier Vialard; Justin Solomon 001 (CoRR, 2016)

Continuous-Flow Graph Transportation Distances. - Justin Solomon 001; Raif M. Rustamov; Leonidas J. Guibas; Adrian Butscher (CoRR, 2016)

Entropic metric alignment for correspondence problems. - Justin Solomon 001; Gabriel Peyré; Vladimir G. Kim; Suvrit Sra (ACM Trans. Graph., 2016)

Parallel Streaming Wasserstein Barycenters. - Matthew Staib; Sebastian Claici; Justin Solomon 001; Stefanie Jegelka (NIPS, 2017)

Learning Detail Transfer based on Geometric Features. - Sema Berkiten; Maciej Halber; Justin Solomon 001; Chongyang Ma; Hao Li 015; Szymon Rusinkiewicz (Comput. Graph. Forum, 2017)

Isometry-Aware Preconditioning for Mesh Parameterization. - Sebastian Claici; Mikhail Bessmeltsev; Scott Schaefer; Justin Solomon 001 (Comput. Graph. Forum, 2017)

GWCNN: A Metric Alignment Layer for Deep Shape Analysis. - Danielle Ezuz; Justin Solomon 001; Vladimir G. Kim; Mirela Ben-Chen (Comput. Graph. Forum, 2017)

Steklov Geometry Processing: An Extrinsic Approach to Spectral Shape Analysis. - Yu Wang 103; Mirela Ben-Chen; Iosif Polterovich; Justin Solomon 001 (CoRR, 2017)

Functional Characterization of Intrinsic and Extrinsic Geometry. - Etienne Corman; Justin Solomon 001; Mirela Ben-Chen; Leonidas J. Guibas; Maks Ovsjanikov (ACM Trans. Graph., 2017)

Boundary Element Octahedral Fields in Volumes. - Justin Solomon 001; Amir Vaxman; David Bommes (ACM Trans. Graph., 2017)

Stochastic Wasserstein Barycenters. - Sebastian Claici; Edward Chien; Justin Solomon 001 (ICML, 2018)

Functional Maps on Product Manifolds. - Emanuele Rodolà; Zorah Lähner; Alex M. Bronstein; Michael M. Bronstein; Justin Solomon 001 (SGP (Posters), 2018)

Interactive Curve Constrained Functional Maps. - Anne Gehre; Michael M. Bronstein; Leif Kobbelt; Justin Solomon 001 (Comput. Graph. Forum, 2018)

Kernel Functional Maps. - Larry Wang; Anne Gehre; Michael M. Bronstein; Justin Solomon 001 (Comput. Graph. Forum, 2018)

Optimal Transport on Discrete Domains. - Justin Solomon 001 (CoRR, 2018)

Gerrymandering and Compactness: Implementation Flexibility and Abuse. - Richard Barnes 002; Justin Solomon 001 (CoRR, 2018)

Wasserstein Coresets for Lipschitz Costs. - Sebastian Claici; Justin Solomon 001 (CoRR, 2018)

Quadratically Regularized Optimal Transport on Graphs. - Montacer Essid; Justin Solomon 001 (SIAM J. Sci. Comput., 2018)

Dynamical optimal transport on discrete surfaces. - Hugo Lavenant; Sebastian Claici; Edward Chien; Justin Solomon 001 (ACM Trans. Graph., 2018)

OptCuts: joint optimization of surface cuts and parameterization. - Minchen Li; Danny M. Kaufman; Vladimir G. Kim; Justin Solomon 001; Alla Sheffer (ACM Trans. Graph., 2018)

Singularity-constrained octahedral fields for hexahedral meshing. - Heng Liu; Paul Zhang; Edward Chien; Justin Solomon 001; David Bommes (ACM Trans. Graph., 2018)

Interactive exploration of design trade-offs. - Adriana Schulz; Harrison Wang; Eitan Grinspun; Justin Solomon 001; Wojciech Matusik (ACM Trans. Graph., 2018)

Deep Closest Point: Learning Representations for Point Cloud Registration. - Yue Wang 041; Justin Solomon 001 (ICCV, 2019)

Learning Embeddings into Entropic Wasserstein Spaces. - Charlie Frogner; Farzaneh Mirzazadeh; Justin Solomon 001 (ICLR (Poster), 2019)

Placental Flattening via Volumetric Parameterization. - Sayed Mazdak Abulnaga; Esra Abaci Turk; Mikhail Bessmeltsev; Patricia Ellen Grant; Justin Solomon 001; Polina Golland (MICCAI (4), 2019)

Alleviating Label Switching with Optimal Transport. - Pierre Monteiller; Sebastian Claici; Edward Chien; Farzaneh Mirzazadeh; Justin M. Solomon; Mikhail Yurochkin (NeurIPS, 2019)

PRNet: Self-Supervised Learning for Partial-to-Partial Registration. - Yue Wang 041; Justin M. Solomon (NeurIPS, 2019)

Hierarchical Optimal Transport for Document Representation. - Mikhail Yurochkin; Sebastian Claici; Edward Chien; Farzaneh Mirzazadeh; Justin M. Solomon (NeurIPS, 2019)

Functional Maps Representation On Product Manifolds. - Emanuele Rodolà; Zorah Lähner; Alexander M. Bronstein; Michael M. Bronstein; Justin Solomon 001 (Comput. Graph. Forum, 2019)

Audio Transport: A Generalized Portamento via Optimal Transport. - Trevor Henderson; Justin Solomon 001 (CoRR, 2019)

Deep Sketch-Based Modeling of Man-Made Shapes. - Dmitriy Smirnov 001; Mikhail Bessmeltsev; Justin Solomon 001 (CoRR, 2019)

Complexity and Geometry of Sampling Connected Graph Partitions. - Lorenzo Najt; Daryl R. DeFord; Justin Solomon 001 (CoRR, 2019)

Recombination: A family of Markov chains for redistricting. - Daryl R. DeFord; Moon Duchin; Justin Solomon 001 (CoRR, 2019)

Total Variation Isoperimetric Profiles. - Daryl R. DeFord; Hugo Lavenant; Zachary Schutzman; Justin Solomon 001 (SIAM J. Appl. Algebra Geom., 2019)

Vectorization of Line Drawings via Polyvector Fields. - Mikhail Bessmeltsev; Justin Solomon 001 (ACM Trans. Graph., 2019)

Reversible Harmonic Maps between Discrete Surfaces. - Danielle Ezuz; Justin Solomon 001; Mirela Ben-Chen (ACM Trans. Graph., 2019)

Optimal transport-based polar interpolation of directional fields. - Justin Solomon 001; Amir Vaxman (ACM Trans. Graph., 2019)

Steklov Spectral Geometry for Extrinsic Shape Analysis. - Yu Wang 103; Mirela Ben-Chen; Iosif Polterovich; Justin Solomon 001 (ACM Trans. Graph., 2019)

Dynamic Graph CNN for Learning on Point Clouds. - Yue Wang 041; Yongbin Sun; Ziwei Liu 002; Sanjay E. Sarma; Michael M. Bronstein; Justin M. Solomon (ACM Trans. Graph., 2019)

Deep Parametric Shape Predictions Using Distance Fields. - Dmitriy Smirnov 001; Matthew Fisher; Vladimir G. Kim; Richard Zhang 001; Justin Solomon 001 (CVPR, 2020)

Pillar-Based Object Detection for Autonomous Driving. - Yue Wang 041; Alireza Fathi; Abhijit Kundu; David A. Ross; Caroline Pantofaru; Thomas A. Funkhouser; Justin Solomon 001 (ECCV (22), 2020)

Model Fusion with Kullback-Leibler Divergence. - Sebastian Claici; Mikhail Yurochkin; Soumya Ghosh; Justin Solomon 001 (ICML, 2020)

Regularized Building Segmentation by Frame Field Learning. - Nicolas Girard; Dmitriy Smirnov 001; Justin Solomon 001; Yuliya Tarabalka (IGARSS, 2020)

Continuous Regularized Wasserstein Barycenters. - Lingxiao Li; Aude Genevay; Mikhail Yurochkin; Justin M. Solomon (NeurIPS, 2020)

Hexahedral Mesh Repair via Sum-of-Squares Relaxation. - Zoë Marschner; David R. Palmer 001; Paul Zhang; Justin Solomon 001 (Comput. Graph. Forum, 2020)

Medial Axis Isoperimetric Profiles. - Paul Zhang; Daryl R. DeFord; Justin Solomon 001 (Comput. Graph. Forum, 2020)

Polygonal Building Segmentation by Frame Field Learning. - Nicolas Girard; Dmitriy Smirnov 001; Justin Solomon 001; Yuliya Tarabalka (CoRR, 2020)

A Computational Approach to Measuring Vote Elasticity and Competitiveness. - Daryl R. DeFord; Moon Duchin; Justin Solomon 001 (CoRR, 2020)

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection. - Yue Wang 041; Alireza Fathi; Jiajun Wu 001; Thomas A. Funkhouser; Justin Solomon 001 (CoRR, 2020)

Redistricting Algorithms. - Amariah Becker; Justin Solomon 001 (CoRR, 2020)

Geometry of Graph Partitions via Optimal Transport. - Tara Abrishami; Nestor Guillen; Parker Rule; Zachary Schutzman; Justin Solomon 001; Thomas Weighill; Si Wu (SIAM J. Sci. Comput., 2020)

Algebraic Representations for Volumetric Frame Fields. - David R. Palmer 001; David Bommes; Justin Solomon 001 (ACM Trans. Graph., 2020)

Octahedral Frames for Feature-Aligned Cross Fields. - Paul Zhang; Josh Vekhter; Edward Chien; David Bommes; Etienne Vouga; Justin Solomon 001 (ACM Trans. Graph., 2020)

DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries. - Yue Wang 041; Vitor Guizilini; Tianyuan Zhang 002; Yilun Wang; Hang Zhao; Justin Solomon 001 (CoRL, 2021)

Polygonal Building Extraction by Frame Field Learning. - Nicolas Girard; Dmitriy Smirnov 001; Justin Solomon 001; Yuliya Tarabalka (CVPR, 2021)

Learning Manifold Patch-Based Representations of Man-Made Shapes. - Dmitriy Smirnov 001; Mikhail Bessmeltsev; Justin Solomon 001 (ICLR, 2021)

Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization. - Alexander Korotin; Lingxiao Li; Justin Solomon 001; Evgeny Burnaev (ICLR, 2021)

Outlier-Robust Optimal Transport. - Debarghya Mukherjee; Aritra Guha; Justin M. Solomon; Yuekai Sun; Mikhail Yurochkin (ICML, 2021)

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark. - Alexander Korotin; Lingxiao Li; Aude Genevay; Justin M. Solomon; Alexander Filippov; Evgeny Burnaev (NeurIPS, 2021)

Large-Scale Wasserstein Gradient Flows. - Petr Mokrov; Alexander Korotin; Lingxiao Li; Aude Genevay; Justin M. Solomon; Evgeny Burnaev (NeurIPS, 2021)

MarioNette: Self-Supervised Sprite Learning. - Dmitriy Smirnov 001; Michaël Gharbi; Matthew Fisher; Vitor Guizilini; Alexei A. Efros; Justin M. Solomon (NeurIPS, 2021)

Object DGCNN: 3D Object Detection using Dynamic Graphs. - Yue Wang 041; Justin M. Solomon (NeurIPS, 2021)

Improving approximate optimal transport distances using quantization. - Gaspard Beugnot; Aude Genevay; Kristjan H. Greenewald; Justin Solomon 001 (UAI, 2021)

Special issue on 14th International Conference on Geometric Modeling and Processing (GMP2020). - Carlotta Giannelli; Lin Lu 001; Justin Solomon 001 (Comput. Aided Geom. Des., 2021)

Frame Field Operators. - David R. Palmer 001; Oded Stein; Justin Solomon 001 (Comput. Graph. Forum, 2021)

Synthesis of Frame Field-Aligned Multi-Laminar Structures. - Florian Cyril Stutz; Tim Felle Olsen; Jeroen Peter Groen; Niels Aage; Ole Sigmund; Justin Solomon 001; Jakob Andreas Bærentzen (CoRR, 2021)

Co-Optimization of Design and Fabrication Plans for Carpentry: Supplemental Material. - Haisen Zhao; Max Willsey; Amy Zhu; Chandrakana Nandi; Zachary Tatlock; Justin Solomon 001; Adriana Schulz (CoRR, 2021)

Incorporating Unlabeled Data into Distributionally Robust Learning. - Charlie Frogner; Sebastian Claici; Edward Chien; Justin Solomon 001 (J. Mach. Learn. Res., 2021)

HodgeNet: learning spectral geometry on triangle meshes. - Dmitriy Smirnov 001; Justin Solomon 001 (ACM Trans. Graph., 2021)

Fast quasi-harmonic weights for geometric data interpolation. - Yu Wang 103; Justin Solomon 001 (ACM Trans. Graph., 2021)

Interactive all-hex meshing via cuboid decomposition. - Lingxiao Li; Paul Zhang; Dmitriy Smirnov 001; S. Mazdak Abulnaga; Justin Solomon 001 (ACM Trans. Graph., 2021)

Pareto gamuts: exploring optimal designs across varying contexts. - Liane Makatura; Minghao Guo; Adriana Schulz; Justin Solomon 001; Wojciech Matusik (ACM Trans. Graph., 2021)

Sum-of-squares geometry processing. - Zoë Marschner; Paul Zhang; David R. Palmer 001; Justin Solomon 001 (ACM Trans. Graph., 2021)

Representation Learning for Object Detection from Unlabeled Point Cloud Sequences. - Xiangru Huang; Yue Wang 041; Vitor Campanholo Guizilini; Rares Andrei Ambrus; Adrien Gaidon; Justin M. Solomon (CoRL, 2022)

DeepCurrents: Learning Implicit Representations of Shapes with Boundaries. - David R. Palmer 001; Dmitriy Smirnov 001; Stephanie Wang; Albert Chern; Justin Solomon 001 (CVPR, 2022)

Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. - Tal Shnitzer; Mikhail Yurochkin; Kristjan H. Greenewald; Justin M. Solomon (ICML, 2022)

Wassersplines for Stylized Neural Animation. - Paul Zhang; Dmitriy Smirnov 001; Justin Solomon 001 (CoRR, 2022)

Symmetric Volume Maps. - S. Mazdak Abulnaga; Oded Stein; Polina Golland; Justin M. Solomon (CoRR, 2022)

A Dataset and Benchmark for Mesh Parameterization. - Georgia Shay; Justin Solomon 001; Oded Stein (CoRR, 2022)

Outlier-Robust Group Inference via Gradient Space Clustering. - Yuchen Zeng; Kristjan H. Greenewald; Kangwook Lee 001; Justin Solomon 001; Mikhail Yurochkin (CoRR, 2022)

$k$-Variance: A Clustered Notion of Variance. - Justin Solomon 001; Kristjan H. Greenewald; Haikady N. Nagaraja (SIAM J. Math. Data Sci., 2022)

Volumetric Parameterization of the Placenta to a Flattened Template. - S. Mazdak Abulnaga; Esra Abaci Turk; Mikhail Bessmeltsev; Patricia Ellen Grant; Justin Solomon 001; Polina Golland (IEEE Trans. Medical Imaging, 2022)

Synthesis of Frame Field-Aligned Multi-Laminar Structures. - Florian Cyril Stutz; Tim Felle Olsen; Jeroen Peter Groen; Tuan Nguyen Trung; Niels Aage; Ole Sigmund; Justin Solomon 001; Jakob Andreas Bærentzen (ACM Trans. Graph., 2022)

Co-Optimization of Design and Fabrication Plans for Carpentry. - Haisen Zhao; Max Willsey; Amy Zhu; Chandrakana Nandi; Zachary Tatlock; Justin Solomon 001; Adriana Schulz (ACM Trans. Graph., 2022)

A Splitting Scheme for Flip-Free Distortion Energies. - Oded Stein; Jiajin Li; Justin Solomon 001 (SIAM J. Imaging Sci., 2022)

Wassersplines for Neural Vector Field-Controlled Animation. - Paul Zhang; Dmitriy Smirnov 001; Justin Solomon 001 (Comput. Graph. Forum, 2022)

Learning Proximal Operators to Discover Multiple Optima. - Lingxiao Li; Noam Aigerman; Vladimir G. Kim; Jiajin Li; Kristjan H. Greenewald; Mikhail Yurochkin; Justin Solomon 001 (ICLR, 2023)

Sampling with Mollified Interaction Energy Descent. - Lingxiao Li; Qiang Liu; Anna Korba; Mikhail Yurochkin; Justin Solomon 001 (ICLR, 2023)

Riemannian Metric Learning via Optimal Transport. - Christopher Scarvelis; Justin Solomon 001 (ICLR, 2023)

Self-Consistent Velocity Matching of Probability Flows. - Lingxiao Li; Samuel Hurault; Justin M. Solomon (NeurIPS, 2023)

A Convex Optimization Framework for Regularized Geodesic Distances. - Michal Edelstein; Nestor Guillen; Justin Solomon 001; Mirela Ben-Chen (SIGGRAPH (Conference Paper Track), 2023)

Data-Free Learning of Reduced-Order Kinematics. - Nicholas Sharp; Cristian Romero; Alec Jacobson; Etienne Vouga; Paul G. Kry; David I. W. Levin; Justin Solomon 001 (SIGGRAPH (Conference Paper Track), 2023)

Sum-of-Squares Collision Detection for Curved Shapes and Paths. - Paul Zhang; Zoë Marschner; Justin Solomon 001; Rasmus Tamstorf (SIGGRAPH (Conference Paper Track), 2023)

Deep Augmentation: Enhancing Self-Supervised Learning through Transformations in Higher Activation Space. - Rickard Brüel Gabrielsson; Tongzhou Wang 001; Manel Baradad; Justin Solomon 001 (CoRR, 2023)

Large Language Model Routing with Benchmark Datasets. - Tal Shnitzer; Anthony Ou; Mírian Silva; Kate Soule; Yuekai Sun; Justin Solomon 001; Neil Thompson; Mikhail Yurochkin (CoRR, 2023)

GeRA: Label-Efficient Geometrically Regularized Alignment. - Dustin Klebe; Tal Shnitzer; Mikhail Yurochkin; Leonid Karlinsky; Justin Solomon 001 (CoRR, 2023)

Rewiring with Positional Encodings for Graph Neural Networks. - Rickard Brüel Gabrielsson; Mikhail Yurochkin; Justin Solomon 001 (Trans. Mach. Learn. Res., 2023)

k-Mixup Regularization for Deep Learning via Optimal Transport. - Kristjan H. Greenewald; Anming Gu; Mikhail Yurochkin; Justin Solomon 001; Edward Chien (Trans. Mach. Learn. Res., 2023)

Symmetric Volume Maps: Order-invariant Volumetric Mesh Correspondence with Free Boundary. - S. Mazdak Abulnaga; Oded Stein; Polina Golland; Justin Solomon 001 (ACM Trans. Graph., 2023)

Variational quasi-harmonic maps for computing diffeomorphisms. - Yu Wang 103; Minghao Guo; Justin Solomon 001 (ACM Trans. Graph., 2023)

Variational Barycentric Coordinates. - Ana Dodik; Oded Stein; Vincent Sitzmann; Justin Solomon 001 (ACM Trans. Graph., 2023)

Slicing Mutual Information Generalization Bounds for Neural Networks. - Kimia Nadjahi; Kristjan H. Greenewald; Rickard Brüel Gabrielsson; Justin Solomon 001 (ICML, 2024)

Asymmetry in Low-Rank Adapters of Foundation Models. - Jiacheng Zhu; Kristjan H. Greenewald; Kimia Nadjahi; Haitz Sáez de Ocáriz Borde; Rickard Brüel Gabrielsson; Leshem Choshen; Marzyeh Ghassemi; Mikhail Yurochkin; Justin Solomon 001 (ICML, 2024)

Score Distillation via Reparametrized DDIM. - Artem Lukoianov; Haitz Sáez de Ocáriz Borde; Kristjan H. Greenewald; Vitor Guizilini; Timur M. Bagautdinov; Vincent Sitzmann; Justin M. Solomon (NeurIPS, 2024)

Nuclear Norm Regularization for Deep Learning. - Christopher Scarvelis; Justin M. Solomon (NeurIPS, 2024)

Robust Biharmonic Skinning Using Geometric Fields. - Ana Dodik; Vincent Sitzmann; Justin Solomon 001; Oded Stein (CoRR, 2024)

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. - Rickard Brüel Gabrielsson; Jiacheng Zhu; Onkar Bhardwaj; Leshem Choshen; Kristjan H. Greenewald; Mikhail Yurochkin; Justin Solomon 001 (CoRR, 2024)

Through the Looking Glass: Mirror Schrödinger Bridges. - Leticia Mattos Da Silva; Silvia Sellán; Justin Solomon 001 (CoRR, 2024)

Lifting Directional Fields to Minimal Sections. - David R. Palmer 001; Albert Chern; Justin Solomon 001 (ACM Trans. Graph., 2024)

A Framework for Solving Parabolic Partial Differential Equations on Discrete Domains. - Leticia Mattos Da Silva; Oded Stein; Justin Solomon 001 (ACM Trans. Graph., 2024)

Deep Augmentation: Dropout as Augmentation for Self-Supervised Learning. - Rickard Brüel Gabrielsson; Tongzhou Wang 001; Manel Baradad; Justin Solomon 001 (Trans. Mach. Learn. Res., 2025)

Closed-Form Diffusion Models. - Christopher Scarvelis; Haitz Sáez de Ocáriz Borde; Justin Solomon 001 (Trans. Mach. Learn. Res., 2025)

Low-Rank Adaptation of Neural Fields. - Anh Truong; Ahmed H. Mahmoud; Mina Konakovic-Lukovic; Justin Solomon 001 (CoRR, 2025)

Meschers: Geometry Processing of Impossible Objects. - Ana Dodik; Isabella Yu; Kartik Chandra; Jonathan Ragan-Kelley; Joshua B. Tenenbaum; Vincent Sitzmann; Justin Solomon 001 (ACM Trans. Graph., 2025)