Alexia Jolicoeur-Martineau

According to our database1, Alexia Jolicoeur-Martineau authored at least 18 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
PopulAtion Parameter Averaging (PAPA).
Trans. Mach. Learn. Res., 2024

Understanding Adam Requires Better Rotation Dependent Assumptions.
CoRR, 2024

Generating Tabular Data Using Heterogeneous Sequential Feature Forest Flow Matching.
CoRR, 2024

Beyond FVD: Enhanced Evaluation Metrics for Video Generation Quality.
CoRR, 2024

Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning Trees.
CoRR, 2024

Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion.
CoRR, 2024

LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters.
CoRR, 2024

Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Diffusion models with location-scale noise.
CoRR, 2023

2022
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback.
CoRR, 2022

MCVD - Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Gotta Go Fast When Generating Data with Score-Based Models.
CoRR, 2021

Adversarial score matching and improved sampling for image generation.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Stochastic Hamiltonian Gradient Methods for Smooth Games.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Relativistic f-Divergences.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs.
CoRR, 2019

The relativistic discriminator: a key element missing from standard GAN.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
GANs beyond divergence minimization.
CoRR, 2018


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