Guillaume Lajoie
@glajoie.bsky.social
1.8K followers
8 following
18 posts
Professor at Université de Montréal & Mila -- Québec AI Institute
mathematics - neuroscience - artificial intelligence
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Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie
Guillaume Lajoie
@glajoie.bsky.social
· Aug 19
Eric Elmoznino
@ericelmoznino.bsky.social
· Aug 18
Defining and quantifying compositional structure
What is compositionality? For those of us working in AI or cognitive neuroscience this question can appear easy at first, but becomes increasingly perplexing the more we think about it. We aren’t shor...
ericelmoznino.github.io
Reposted by Guillaume Lajoie
SilicoLabs
@silicolabs.bsky.social
· Jul 17
Modernizing Cognitive Health Research with SilicoLabs | Mila
Cognitive health research is a field dedicated to understanding how our brains work when we think, remember, and learn as we go through life. When combined with medical research and rehabilitation…
mila.quebec
Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie
Shahab Bakhtiari
@shahabbakht.bsky.social
· May 14
Reposted by Guillaume Lajoie
Guillaume Lajoie
@glajoie.bsky.social
· Apr 11
Reposted by Guillaume Lajoie
Sarthak Mittal
@sarthmit.bsky.social
· Feb 28
Amortized In-Context Bayesian Posterior Estimation
Bayesian inference provides a natural way of incorporating prior beliefs and assigning a probability measure to the space of hypotheses. Current solutions rely on iterative routines like Markov Chain ...
arxiv.org
Reposted by Guillaume Lajoie
Sarthak Mittal
@sarthmit.bsky.social
· Feb 28
In-Context Parametric Inference: Point or Distribution Estimators?
Bayesian and frequentist inference are two fundamental paradigms in statistical estimation. Bayesian methods treat hypotheses as random variables, incorporating priors and updating beliefs via Bayes' ...
arxiv.org
Reposted by Guillaume Lajoie
Erica Busch
@elbusch.bsky.social
· Apr 3
Accelerated learning of a noninvasive human brain-computer interface via manifold geometry
Brain-computer interfaces (BCIs) promise to restore and enhance a wide range of human capabilities. However, a barrier to the adoption of BCIs is how long it can take users to learn to control them. W...
doi.org
Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie
Guillaume Lajoie
@glajoie.bsky.social
· Feb 28
Sarthak Mittal
@sarthmit.bsky.social
· Feb 28
In-Context Parametric Inference: Point or Distribution Estimators?
Bayesian and frequentist inference are two fundamental paradigms in statistical estimation. Bayesian methods treat hypotheses as random variables, incorporating priors and updating beliefs via Bayes' ...
arxiv.org
Reposted by Guillaume Lajoie
Reposted by Guillaume Lajoie