Justin M. Solomon

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 19

Top Topics

Supervised Learning

Object Detection

Top Venues

ACM Trans. Graph.

Publications

Lingxiao Li, Samuel Hurault, Justin M. Solomon
Self-Consistent Velocity Matching of Probability Flows. NeurIPS (2023)
S. Mazdak Abulnaga, Oded Stein, Polina Golland, Justin M. Solomon
Symmetric Volume Maps. CoRR (2022)
Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. ICML (2022)
Xiangru Huang, Yue Wang, Vitor Campanholo Guizilini, Rares Andrei Ambrus, Adrien Gaidon, Justin M. Solomon
Representation Learning for Object Detection from Unlabeled Point Cloud Sequences. CoRL (2022)
Yue Wang, Justin M. Solomon
Object DGCNN: 3D Object Detection using Dynamic Graphs. NeurIPS (2021)
Debarghya Mukherjee, Aritra Guha, Justin M. Solomon, Yuekai Sun, Mikhail Yurochkin
Outlier-Robust Optimal Transport. ICML (2021)
Dmitriy Smirnov, Justin M. Solomon
HodgeNet: Learning Spectral Geometry on Triangle Meshes. CoRR (2021)
Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M. Solomon, Alexander Filippov, Evgeny Burnaev
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark. NeurIPS (2021)
Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M. Solomon, Evgeny Burnaev
Large-Scale Wasserstein Gradient Flows. NeurIPS (2021)
Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Alexei A. Efros, Justin M. Solomon
MarioNette: Self-Supervised Sprite Learning. NeurIPS (2021)
David R. Palmer, Dmitriy Smirnov, Stephanie Wang, Albert Chern, Justin M. Solomon
DeepCurrents: Learning Implicit Representations of Shapes with Boundaries. CoRR (2021)
Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M. Solomon
Continuous Regularized Wasserstein Barycenters. NeurIPS (2020)
Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon, Mikhail Yurochkin
Alleviating Label Switching with Optimal Transport. NeurIPS (2019)
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon
Dynamic Graph CNN for Learning on Point Clouds. ACM Trans. Graph. 38 (5) (2019)
Yue Wang, Justin M. Solomon
PRNet: Self-Supervised Learning for Partial-to-Partial Registration. CoRR (2019)
Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon
Hierarchical Optimal Transport for Document Representation. NeurIPS (2019)
Yue Wang, Justin M. Solomon
Deep Closest Point: Learning Representations for Point Cloud Registration. CoRR (2019)
Yue Wang, Justin M. Solomon
PRNet: Self-Supervised Learning for Partial-to-Partial Registration. NeurIPS (2019)
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon
Dynamic Graph CNN for Learning on Point Clouds. CoRR (2018)