Marc T. Law
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
9
Active years
2012–2025
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Neural Spacetimes for DAG Representation Learning. | Haitz Sez de Ocriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein |
| 2024 | ICLR | Graph Metanetworks for Processing Diverse Neural Architectures. | Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas |
| 2024 | SiggraphA | SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes. | Tianchang Shen, Zhaoshuo Li, Marc T. Law, Matan Atzmon, Sanja Fidler, James Lucas, Jun Gao, Nicholas Sharp |
| 2023 | ICLR | Spacetime Representation Learning. | Marc T. Law, James Lucas |
| 2022 | CVPR | How Much More Data Do I Need? Estimating Requirements for Downstream Tasks. | Rafid Mahmood, James Lucas, David Acuna, Daiqing Li, Jonah Philion, Jos M. lvarez, Zhiding Yu, Sanja Fidler, Marc T. Law |
| 2022 | ICLR | Domain Adversarial Training: A Game Perspective. | David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler |
| 2022 | ICLR | Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. | Rafid Mahmood, Sanja Fidler, Marc T. Law |
| 2021 | ICCV | Self-Supervised Real-to-Sim Scene Generation. | Aayush Prakash, Shoubhik Debnath, Jean-Francois Lafleche, Eric Cameracci, Gavriel State, Stan Birchfield, Marc T. Law |
| 2021 | ICML | f-Domain Adversarial Learning: Theory and Algorithms. | David Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler |
| 2020 | ICLR | A Theoretical Analysis of the Number of Shots in Few-Shot Learning. | Tianshi Cao, Marc T. Law, Sanja Fidler |
| 2019 | ICASSP | Centroid-based Deep Metric Learning for Speaker Recognition. | Jixuan Wang, Kuan-Chieh Wang, Marc T. Law, Frank Rudzicz, Michael Brudno |
| 2019 | ICCV | Video Face Clustering With Unknown Number of Clusters. | Makarand Tapaswi, Marc T. Law, Sanja Fidler |
| 2019 | ICLR | Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. | Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel |
| 2018 | ICPR | Representing Relative Visual Attributes with a Reference-Point-Based Decision Model. | Marc T. Law, Paul Weng |
| 2017 | CVPR | Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. | Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing |
| 2017 | ICML | Deep Spectral Clustering Learning. | Marc T. Law, Raquel Urtasun, Richard S. Zemel |
| 2016 | CVPR | Closed-Form Training of Mahalanobis Distance for Supervised Clustering. | Marc T. Law, Yaoliang Yu, Matthieu Cord, Eric P. Xing |
| 2014 | CVPR | Fantope Regularization in Metric Learning. | Marc T. Law, Nicolas Thome, Matthieu Cord |
| 2013 | ICCV | Quadruplet-Wise Image Similarity Learning. | Marc T. Law, Nicolas Thome, Matthieu Cord |
| 2012 | CBMI | Structural and visual similarity learning for Web page archiving. | Marc T. Law, Carlos Sureda Gutierrez, Nicolas Thome, Stphane Ganarski |
| 2012 | ECCV | Hybrid Pooling Fusion in the BoW Pipeline. | Marc T. Law, Nicolas Thome, Matthieu Cord |