no code implementations • ICML 2020 • samuel cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Deisenroth
Gaussian processes (GPs) are nonparametric Bayesian models that have been applied to regression and classification problems.
no code implementations • 20 Jul 2023 • Ilana Sebag, samuel cohen, Marc Peter Deisenroth
One of the key approaches to IL is to define a distance between agent and expert and to find an agent policy that minimizes that distance.
1 code implementation • 24 Mar 2023 • Yicheng Luo, Zhengyao Jiang, samuel cohen, Edward Grefenstette, Marc Peter Deisenroth
In this paper, we introduce Optimal Transport Reward labeling (OTR), an algorithm that assigns rewards to offline trajectories, with a few high-quality demonstrations.
1 code implementation • 8 Feb 2023 • samuel cohen, Marc Sabaté Vidales, David Šiška, Łukasz Szpruch
We investigate whether the fee income from trades on the CFM is sufficient for the liquidity providers to hedge away the exposure to market risk.
no code implementations • 11 Jul 2022 • Heli Ben-Hamu, samuel cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky T. Q. Chen, Yaron Lipman
Continuous Normalizing Flows (CNFs) are a class of generative models that transform a prior distribution to a model distribution by solving an ordinary differential equation (ODE).
1 code implementation • 10 Jun 2022 • Brandon Amos, samuel cohen, Giulia Luise, Ievgen Redko
We study the use of amortized optimization to predict optimal transport (OT) maps from the input measures, which we call Meta OT.
1 code implementation • ICLR 2022 • Arnaud Fickinger, samuel cohen, Stuart Russell, Brandon Amos
Cross-domain imitation learning studies how to leverage expert demonstrations of one agent to train an imitation agent with a different embodiment or morphology.
no code implementations • 29 Sep 2021 • samuel cohen, Brandon Amos, Marc Peter Deisenroth, Mikael Henaff, Eugene Vinitsky, Denis Yarats
In this setting, we explore recipes for imitation learning based on adversarial learning and optimal transport.
1 code implementation • 18 Jun 2021 • 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.
1 code implementation • 14 Feb 2021 • samuel cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
Gaussian processes (GPs) are nonparametric Bayesian models that have been applied to regression and classification problems.
no code implementations • 14 Feb 2021 • samuel cohen, Alexander Terenin, Yannik Pitcan, Brandon Amos, Marc Peter Deisenroth, K S Sesh Kumar
To construct this distance, we introduce a characterization of the one-dimensional multi-marginal Kantorovich problem and use it to highlight a number of properties of the sliced multi-marginal Wasserstein distance.
no code implementations • 8 Feb 2021 • samuel cohen, Tanut Treetanthiploet
The Asymptotic Randomised Control (ARC) algorithm provides a rigorous approximation to the optimal strategy for a wide class of Bayesian bandits, while retaining low computational complexity.
no code implementations • 14 Jul 2020 • Samuel Cohen, Michael Arbel, Marc Peter Deisenroth
Barycentric averaging is a principled way of summarizing populations of measures.
1 code implementation • 22 Jun 2020 • Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
Dynamic time warping (DTW) is a useful method for aligning, comparing and combining time series, but it requires them to live in comparable spaces.
no code implementations • 18 Jun 2019 • Emre Yilmaz, Samuel Cohen, Xianghu Yue, David van Leeuwen, Haizhou Li
This archive contains recordings with monolingual Frisian and Dutch speech segments as well as Frisian-Dutch CS speech, hence the recognition performance on monolingual segments is also vital for accurate transcriptions.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2