7 citations · 13 across the 8 of their papers we have counts for
8 papers
Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
Marco Jiralerspong, Esther Derman, Danilo Vucetic +5
A major bottleneck in scientific discovery consists of narrowing an exponentially large set of objects, such as proteins or molecules, to a small set of promising candidates with d…
General Causal Imputation via Synthetic Interventions
Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah +2
Given two sets of elements (such as cell types and drug compounds), researchers typically only have access to a limited subset of their interactions. The task of causal imputation…
Expected flow networks in stochastic environments and two-player zero-sum games
Marco Jiralerspong, Bilun Sun, Danilo Vucetic +4
Generative flow networks (GFlowNets) are sequential sampling models trained to match a given distribution. GFlowNets have been successfully applied to various structured object gen…
On the Stability of Iterative Retraining of Generative Models on their own Data
Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis +2
Deep generative models have made tremendous progress in modeling complex data, often exhibiting generation quality that surpasses a typical human's ability to discern the authentic…
AI4GCC -- Track 3: Consumption and the Challenges of Multi-Agent RL
Marco Jiralerspong, Gauthier Gidel
The AI4GCC competition presents a bold step forward in the direction of integrating machine learning with traditional economic policy analysis. Below, we highlight two potential ar…
Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples
Marco Jiralerspong, Avishek Joey Bose, Ian Gemp +3
The past few years have seen impressive progress in the development of deep generative models capable of producing high-dimensional, complex, and photo-realistic data. However, cur…
Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms
Marco Jiralerspong, Gauthier Gidel
We describe our approach for the generative emotional vocal burst task (ExVo Generate) of the ICML Expressive Vocalizations Competition. We train a conditional StyleGAN2 architectu…
The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts
Alice Baird, Panagiotis Tzirakis, Gauthier Gidel +7
The ICML Expressive Vocalization (ExVo) Competition is focused on understanding and generating vocal bursts: laughs, gasps, cries, and other non-verbal vocalizations that are centr…