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- Université de MontréalCA125 papers
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- Flatiron Health (United States)US24 papers
- Flatiron Institute23 papers
- Centre National de la Recherche ScientifiqueFR22 papers
- University of TorontoCA16 papers
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26 papers · 1 filter
Inferring the immune response from repertoire sequencing
Maximilian Puelma Touzel, Aleksandra M. Walczak, Thierry Mora
High-throughput sequencing of B- and T-cell receptors makes it possible to track immune repertoires across time, in different tissues, and in acute and chronic diseases or in healt…
Joint Learning of Generative Translator and Classifier for Visually Similar Classes
ByungIn Yoo, Tristan Sylvain, Yoshua Bengio +1
In this paper, we propose a Generative Translation Classification Network (GTCN) for improving visual classification accuracy in settings where classes are visually similar and dat…
Continuous Graph Neural Networks
Louis-Pascal A. C. Xhonneux, Meng Qu, Jian Tang
This paper builds on the connection between graph neural networks and traditional dynamical systems. We propose continuous graph neural networks (CGNN), which generalise existing g…
Online Learned Continual Compression with Adaptive Quantization Modules
Lucas Caccia, Eugene Belilovsky, Massimo Caccia +1
We introduce and study the problem of Online Continual Compression, where one attempts to simultaneously learn to compress and store a representative dataset from a non i.i.d data…
Two-Step Sound Source Separation: Training on Learned Latent Targets
Efthymios Tzinis, Shrikant Venkataramani, Zhepei Wang +2
In this paper, we propose a two-step training procedure for source separation via a deep neural network. In the first step we learn a transform (and it's inverse) to a latent space…
Cleaning our own Dust: Simulating and Separating Galactic Dust Foregrounds with Neural Networks
K. Aylor, M. Haq, L. Knox +2
Separating galactic foreground emission from maps of the cosmic microwave background (CMB), and quantifying the uncertainty in the CMB maps due to errors in foreground separation a…