90 citations · 332 across the 63 of their papers we have counts for
5 papers · 1 filter
The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski
Invariant Causal Prediction (Peters et al., 2016) is a technique for out-of-distribution generalization which assumes that some aspects of the data distribution vary across the tra…
Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Normalizing flows are among the most popular paradigms in generative modeling, especially for images, primarily because we can efficiently evaluate the likelihood of a data point.…
Efficient sampling from the Bingham distribution
Rong Ge, Holden Lee, Jianfeng Lu +1
We give a algorithm for exact sampling from the Bingham distribution on the sphere with expected runtime of $\operatorname{poly}(d…
On Learning Language-Invariant Representations for Universal Machine Translation
Han Zhao, Junjie Hu, Andrej Risteski
The goal of universal machine translation is to learn to translate between any pair of languages, given a corpus of paired translated documents for \emph{a small subset} of all pai…
Fast Convergence for Langevin Diffusion with Manifold Structure
Ankur Moitra, Andrej Risteski
In this paper, we study the problem of sampling from distributions of the form p(x) \propto e^{-βf(x)} for some function f whose values and gradients we can query. This mode of acc…