28 citations · 90 across the 11 of their papers we have counts for
5 papers · 1 filter
SamToNe: Improving Contrastive Loss for Dual Encoder Retrieval Models with Same Tower Negatives
Fedor Moiseev, Gustavo Hernandez Abrego, Peter Dornbach +3
Dual encoders have been used for retrieval tasks and representation learning with good results. A standard way to train dual encoders is using a contrastive loss with in-batch nega…
Coupled Gradient Estimators for Discrete Latent Variables
Zhe Dong, Andriy Mnih, George Tucker
Training models with discrete latent variables is challenging due to the high variance of unbiased gradient estimators. While low-variance reparameterization gradients of a continu…
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…
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems
Zhe Dong, Bryan A. Seybold, Kevin P. Murphy +1
We propose an efficient inference method for switching nonlinear dynamical systems. The key idea is to learn an inference network which can be used as a proposal distribution for t…
On Predictive Information in RNNs
Zhe Dong, Deniz Oktay, Ben Poole +1
Certain biological neurons demonstrate a remarkable capability to optimally compress the history of sensory inputs while being maximally informative about the future. In this work,…