5 citations · 9 across the 4 of their papers we have counts for
6 papers
Riemannian Convex Potential Maps
Samuel Cohen, Brandon Amos, Yaron Lipman
Modeling distributions on Riemannian manifolds is a crucial component in understanding non-Euclidean data that arises, e.g., in physics and geology. The budding approaches in this…
Identifiability in inverse reinforcement learning
Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch
Inverse reinforcement learning attempts to reconstruct the reward function in a Markov decision problem, using observations of agent actions. As already observed in Russell [1998]…
Healing Products of Gaussian Processes
Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala +1
Gaussian processes (GPs) are nonparametric Bayesian models that have been applied to regression and classification problems. One of the approaches to alleviate their cubic training…
Estimating Barycenters of Measures in High Dimensions
Samuel Cohen, Michael Arbel, Marc Peter Deisenroth
Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters typically parametrize them as weighted sums of Dira…
Aligning Time Series on Incomparable Spaces
Samuel Cohen, Giulia Luise, Alexander Terenin +2
Dynamic time warping (DTW) is a useful method for aligning, comparing and combining time series, but it requires them to live in comparable spaces. In this work, we consider a sett…
Multi-Graph Decoding for Code-Switching ASR
Emre Yılmaz, Samuel Cohen, Xianghu Yue +2
In the FAME! Project, a code-switching (CS) automatic speech recognition (ASR) system for Frisian-Dutch speech is developed that can accurately transcribe the local broadcaster's b…