Marc T. Law

Affiliations:
  • NVIDIA Toronto AI Lab, ON, Canada
  • University of Toronto, Canada
  • Vector Institute, Toronto, ON, Canada
  • Pierre and Marie Curie University, Paris, France (PhD 2015)
  • Sorbonne University, LIP6, Paris, France


According to our database1, Marc T. Law authored at least 36 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Uncertainty Estimation for 3D Object Detection via Evidential Learning.
CoRR, 2024

Neural Spacetimes for DAG Representation Learning.
CoRR, 2024

Breaking the Curse of Dimensionality with Distributed Neural Computation.
CoRR, 2024

SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes.
Proceedings of the SIGGRAPH Asia 2024 Conference Papers, 2024

Graph Metanetworks for Processing Diverse Neural Architectures.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting.
Trans. Mach. Learn. Res., 2023

Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting.
CoRR, 2023

Spacetime Representation Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Optimizing Data Collection for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Domain Adversarial Training: A Game Perspective.
Proceedings of the Tenth International Conference on Learning Representations, 2022

How Much More Data Do I Need? Estimating Requirements for Downstream Tasks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Ultrahyperbolic Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Feature generation for long-tail classification.
Proceedings of the ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing, Jodhpur, India, December 19, 2021

f-Domain Adversarial Learning: Theory and Algorithms.
Proceedings of the 38th International Conference on Machine Learning, 2021

Self-Supervised Real-to-Sim Scene Generation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Sim2SG: Sim-to-Real Scene Graph Generation for Transfer Learning.
CoRR, 2020

Ultrahyperbolic Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Theoretical Analysis of the Number of Shots in Few-Shot Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Lorentzian Distance Learning for Hyperbolic Representations.
Proceedings of the 36th International Conference on Machine Learning, 2019

Dimensionality Reduction for Representing the Knowledge of Probabilistic Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

Video Face Clustering With Unknown Number of Clusters.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Centroid-based Deep Metric Learning for Speaker Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Representing Relative Visual Attributes with a Reference-Point-Based Decision Model.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017
Learning a Distance Metric from Relative Comparisons between Quadruplets of Images.
Int. J. Comput. Vis., 2017

Deep Spectral Clustering Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Efficient Multiple Instance Metric Learning Using Weakly Supervised Data.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Closed-Form Training of Mahalanobis Distance for Supervised Clustering.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web).
PhD thesis, 2015

Apprentissage de métrique appliqué à la détection de changement de page Web et aux attributs relatifs.
Proceedings of the CORIA 2015 - Conférence en Recherche d'Infomations et Applications, 2015

2014
Bag-of-Words Image Representation: Key Ideas and Further Insight.
Proceedings of the Fusion in Computer Vision - Understanding Complex Visual Content, 2014

Fantope Regularization in Metric Learning.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Quadruplet-Wise Image Similarity Learning.
Proceedings of the IEEE International Conference on Computer Vision, 2013

2012
Hybrid Pooling Fusion in the BoW Pipeline.
Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

Structural and visual comparisons for web page archiving.
Proceedings of the ACM Symposium on Document Engineering, 2012

Structural and visual similarity learning for Web page archiving.
Proceedings of the 10th International Workshop on Content-Based Multimedia Indexing, 2012


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