30 citations · 85 across the 6 of their papers we have counts for
7 papers · 1 filter
Schrödinger Bridge Flow for Unpaired Data Translation
Valentin De Bortoli, Iryna Korshunova, Andriy Mnih +1
Mass transport problems arise in many areas of machine learning whereby one wants to compute a map transporting one distribution to another. Generative modeling techniques like Gen…
DisARM: An Antithetic Gradient Estimator for Binary Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
Training models with discrete latent variables is challenging due to the difficulty of estimating the gradients accurately. Much of the recent progress has been achieved by taking…
Q-Learning in enormous action spaces via amortized approximate maximization
Tom Van de Wiele, David Warde-Farley, Andriy Mnih +1
Applying Q-learning to high-dimensional or continuous action spaces can be difficult due to the required maximization over the set of possible actions. Motivated by techniques from…
Attentive Neural Processes
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz +5
Neural Processes (NPs) (Garnelo et al 2018a;b) approach regression by learning to map a context set of observed input-output pairs to a distribution over regression functions. Each…
Implicit Reparameterization Gradients
Michael Figurnov, Shakir Mohamed, Andriy Mnih
By providing a simple and efficient way of computing low-variance gradients of continuous random variables, the reparameterization trick has become the technique of choice for trai…
Variational Memory Addressing in Generative Models
Jörg Bornschein, Andriy Mnih, Daniel Zoran +1
Aiming to augment generative models with external memory, we interpret the output of a memory module with stochastic addressing as a conditional mixture distribution, where a read…