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05/22/2023
A Convex Optimization Framework for Regularized Geodesic Distances
We propose a general convex optimization problem for computing regulariz...
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05/05/2023
Data-Free Learning of Reduced-Order Kinematics
Physical systems ranging from elastic bodies to kinematic linkages are d...
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03/25/2023
Deep Augmentation: Enhancing Self-Supervised Learning through Transformations in Higher Activation Space
We introduce Deep Augmentation, an approach to data augmentation using d...
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01/31/2023
Self-Consistent Velocity Matching of Probability Flows
We present a discretization-free scalable framework for solving a large ...
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10/24/2022
Sampling with Mollified Interaction Energy Descent
Sampling from a target measure whose density is only known up to a norma...
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10/13/2022
Outlier-Robust Group Inference via Gradient Space Clustering
Traditional machine learning models focus on achieving good performance ...
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08/02/2022
A Dataset and Benchmark for Mesh Parameterization
UV parameterization is a core task in computer graphics, with applicatio...
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05/18/2022
Riemannian Metric Learning via Optimal Transport
We introduce an optimal transport-based model for learning a metric tens...
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02/05/2022
Symmetric Volume Maps
Although shape correspondence is a central problem in geometry processin...
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02/03/2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
The need for efficiently comparing and representing datasets with unknow...
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01/29/2022
Rewiring with Positional Encodings for Graph Neural Networks
Several recent works use positional encodings to extend the receptive fi...
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01/28/2022
Learning Proximal Operators to Discover Multiple Optima
Finding multiple solutions of non-convex optimization problems is a ubiq...
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01/28/2022
Wassersplines for Stylized Neural Animation
Much of computer-generated animation is created by manipulating meshes w...
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11/17/2021
DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
Recent techniques have been successful in reconstructing surfaces as lev...
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11/15/2021
Volumetric Parameterization of the Placenta to a Flattened Template
We present a volumetric mesh-based algorithm for parameterizing the plac...
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10/16/2021
Sum-of-Squares Geometry Processing
Geometry processing presents a variety of difficult numerical problems, ...
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10/13/2021
Object DGCNN: 3D Object Detection using Dynamic Graphs
3D object detection often involves complicated training and testing pipe...
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10/13/2021
DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
We introduce a framework for multi-camera 3D object detection. In contra...
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09/13/2021
Interactive All-Hex Meshing via Cuboid Decomposition
Standard PolyCube-based hexahedral (hex) meshing methods aim to deform t...
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07/30/2021
Co-Optimization of Design and Fabrication Plans for Carpentry: Supplemental Material
Past work on optimizing fabrication plans given a carpentry design can p...
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07/26/2021
Co-Optimization of Design and Fabrication Plans for Carpentry
Past work on optimizing fabrication plans given a carpentry design can p...
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07/12/2021
A Splitting Scheme for Flip-Free Distortion Energies
We introduce a robust optimization method for flip-free distortion energ...
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06/28/2021
Frame Field Operators
Differential operators are widely used in geometry processing for proble...
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06/05/2021
k-Mixup Regularization for Deep Learning via Optimal Transport
Mixup is a popular regularization technique for training deep neural net...
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06/03/2021
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
Despite the recent popularity of neural network-based solvers for optima...
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06/01/2021
Large-Scale Wasserstein Gradient Flows
Wasserstein gradient flows provide a powerful means of understanding and...
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04/29/2021
MarioNette: Self-Supervised Sprite Learning
Visual content often contains recurring elements. Text is made up of gly...
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04/26/2021
HodgeNet: Learning Spectral Geometry on Triangle Meshes
Constrained by the limitations of learning toolkits engineered for other...
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04/12/2021
Synthesis of Frame Field-Aligned Multi-Laminar Structures
In the field of topology optimization, the homogenization approach has b...
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02/25/2021
Improving Approximate Optimal Transport Distances using Quantization
Optimal transport (OT) is a popular tool in machine learning to compare ...
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02/02/2021
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Wasserstein barycenters provide a geometric notion of the weighted avera...
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12/14/2020
Outlier-Robust Optimal Transport
Optimal transport (OT) provides a way of measuring distances between dis...
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12/13/2020
k-Variance: A Clustered Notion of Variance
We introduce k-variance, a generalization of variance built on the machi...
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11/18/2020
Redistricting Algorithms
Why not have a computer just draw a map? This is something you hear a lo...
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09/24/2020
Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection
A common dilemma in 3D object detection for autonomous driving is that h...
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08/28/2020
Continuous Regularized Wasserstein Barycenters
Wasserstein barycenters provide a geometrically meaningful way to aggreg...
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07/20/2020
Pillar-based Object Detection for Autonomous Driving
We present a simple and flexible object detection framework optimized fo...
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07/19/2020
Octahedral Frames for Feature-Aligned Cross-Fields
We present a method for designing smooth cross fields on surfaces that a...
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07/13/2020
Model Fusion with Kullback–Leibler Divergence
We propose a method to fuse posterior distributions learned from heterog...
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07/02/2020
Medial Axis Isoperimetric Profiles
Recently proposed as a stable means of evaluating geometric compactness,...
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05/26/2020
A Computational Approach to Measuring Vote Elasticity and Competitiveness
The recent wave of attention to partisan gerrymandering has come with a ...
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04/30/2020
Polygonal Building Segmentation by Frame Field Learning
While state of the art image segmentation models typically output segmen...
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01/22/2020
Automatic phantom test pattern classification through transfer learning with deep neural networks
Imaging phantoms are test patterns used to measure image quality in comp...
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12/16/2019
Incorporating Unlabeled Data into Distributionally Robust Learning
We study a robust alternative to empirical risk minimization called dist...
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11/05/2019
Alleviating Label Switching with Optimal Transport
Label switching is a phenomenon arising in mixture model posterior infer...
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10/31/2019
Recombination: A family of Markov chains for redistricting
Redistricting is the problem of partitioning a set of geographical units...
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10/21/2019
Geometry of Graph Partitions via Optimal Transport
We define a distance metric between partitions of a graph using machiner...
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08/23/2019
Complexity and Geometry of Sampling Connected Graph Partitions
In this paper, we prove intractability results about sampling from the s...
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08/15/2019
Algebraic Representations for Volumetric Frame Fields
Field-guided parametrization methods have proven effective for quad mesh...
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06/28/2019
