Search Results for author: samuel cohen

Found 15 papers, 7 papers with code

Healing Gaussian Process Experts

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.

Gaussian Processes General Classification +2

On Combining Expert Demonstrations in Imitation Learning via Optimal Transport

no code implementations20 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.

Imitation Learning OpenAI Gym

Optimal Transport for Offline Imitation Learning

1 code implementation24 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.

D4RL Imitation Learning +2

Inefficiency of CFMs: hedging perspective and agent-based simulations

1 code implementation8 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.

Matching Normalizing Flows and Probability Paths on Manifolds

no code implementations11 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).

Meta Optimal Transport

1 code implementation10 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.

Cross-Domain Imitation Learning via Optimal Transport

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.

Continuous Control Imitation Learning

Riemannian Convex Potential Maps

1 code implementation18 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.

Sliced Multi-Marginal Optimal Transport

no code implementations14 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.

Density Estimation Multi-Task Learning

Healing Products of Gaussian Processes

1 code implementation14 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.

Gaussian Processes General Classification +2

Generalised correlated batched bandits via the ARC algorithm with application to dynamic pricing

no code implementations8 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.

Estimating Barycenters of Measures in High Dimensions

no code implementations14 Jul 2020 Samuel Cohen, Michael Arbel, Marc Peter Deisenroth

Barycentric averaging is a principled way of summarizing populations of measures.

Vocal Bursts Intensity Prediction

Aligning Time Series on Incomparable Spaces

1 code implementation22 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.

Dynamic Time Warping Imitation Learning +2

Multi-Graph Decoding for Code-Switching ASR

no code implementations18 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

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