122 citations · 162 across the 12 of their papers we have counts for
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Relative Trajectory Balance is equivalent to Trust-PCL
Tristan Deleu, Padideh Nouri, Yoshua Bengio +1
Recent progress in generative modeling has highlighted the importance of Reinforcement Learning (RL) for fine-tuning, with KL-regularized methods in particular proving to be highly…
Generative Flow Networks: Theory and Applications to Structure Learning
Tristan Deleu
Without any assumptions about data generation, multiple causal models may explain our observations equally well. To avoid selecting a single arbitrary model that could result in un…
Learning Latent Structural Causal Models
Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth +5
Causal learning has long concerned itself with the accurate recovery of underlying causal mechanisms. Such causal modelling enables better explanations of out-of-distribution data.…
Continuous-Time Meta-Learning with Forward Mode Differentiation
Tristan Deleu, David Kanaa, Leo Feng +4
Drawing inspiration from gradient-based meta-learning methods with infinitely small gradient steps, we introduce Continuous-Time Meta-Learning (COMLN), a meta-learning algorithm wh…
Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj +20
The COVID-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries and resulting in widespread lockdowns for emergency containment. Large-sca…
Curriculum in Gradient-Based Meta-Reinforcement Learning
Bhairav Mehta, Tristan Deleu, Sharath Chandra Raparthy +2
Gradient-based meta-learners such as Model-Agnostic Meta-Learning (MAML) have shown strong few-shot performance in supervised and reinforcement learning settings. However, specific…