1 to 10 of 19 Results
Jan 10, 2024
Jin, Zhijing, 2023, "Supplementary data for Corr2Cause: "Can Large Language Models Infer Causation from Correlation?"", https://doi.org/10.17617/3.VYGWHY, Edmond, V3
Paper: "Can Large Language Models Infer Causation from Correlation?" (2023) by Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona Diab*, Bernhard Schölkopf*. (http://arxiv.org/abs/2306.05836) Abstract: Causal inference is one of the hallmarks... |
Nov 5, 2023
Gong, Yijie; Javot, Bernard; Lauer, Anja Patricia Regina; Sawodny, Oliver; Kuchenbecker, Katherine J., 2023, "User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception", https://doi.org/10.17617/3.PAFGCA, Edmond, V1
We encourage viewers to select the "Tree" view, rather than "Table" view, in order to see the files organized by their respective folders. The dataset includes the following: 1. A readme file explaining our user study and the data, 2. Raw acceleration data, 3. Raw robot data, 4.... |
Sep 6, 2023
Gebhard, Timothy, 2023, "Datasets and experimental results for "Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks"", https://doi.org/10.17617/3.K2CY3M, Edmond, V1
This dataset contains the training data and experimental results (i.e. trained models and results on the test set) for the research paper “Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks” by T. D. Gebhard et al. which has been accepted f... |
Jul 26, 2023
Man-Singh-Pradhan, Nayan; Frank, Patrick; Mo, An; Badri-Spröwitz, Alexander, 2023, "Data for Upside down: an open-source motion platform for highly dynamic movement", https://doi.org/10.17617/3.P9GM9Z, Edmond, V1
Dataset contains simulation model, control program, and CAD model of the motion platform. Publication link: https://doi.org/10.48550/arXiv.2303.17974 |
Jul 14, 2023
Gürtler, Nico, 2023, "Training checkpoints for the TriFinger Cube Push and Lift tasks", https://doi.org/10.17617/3.JA8ZW4, Edmond, V1
Training checkpoints for policies trained in Isaac Gym simulation of the TriFinger robotics platform. Checkpoints are available for two tasks: (i) Push a cube to a goal position on the ground, (ii) Lift a cube to goal position and orientation in the air. The checkpoints can be us... |
Jun 22, 2023
Johnson, Brian K.; Naris, Mantas; Sundaram, Vani; Volchko, Angie; Ly, Khoi; Mitchell, Shane K.; Acome, Eric; Kellaris, Nicholas; Keplinger, Christoph; Correll, Nikolaus; Humbert, J. Sean; Rentschler, Mark, 2023, "Data set: A multifunctional soft robotic shape display with high-speed actuation, sensing, and control", https://doi.org/10.17617/3.9S0O4Q, Edmond, V1
Dataset used to generate plots and additional data for the manuscript "A multifunctional soft robotic shape display with high-speed actuation, sensing, and control." The dataset contains several subdirectories with readme files describing the format and structure of the data for... |
Jun 8, 2023
Visona, Giovanni, 2023, "Data for reproducing the training of eDICE model ("Getting Personal with Epigenetics: Towards Individual-specific Epigenomic Imputation with Machine Learning")", https://doi.org/10.17617/3.VKEFB6, Edmond, V3
Data repository for the files needed to reproduce the results in the paper "Getting Personal with Epigenetics: Towards Individual-specific Epigenomic Imputation with Machine Learning", Hawkins-Hooker et al. |
Jun 5, 2023
Jin, Zhijing, 2023, "covid_twitter_data", https://doi.org/10.17617/3.TYNBEQ, Edmond, V1
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May 26, 2023
Hardt, 2023, "The Pile Roberta Large Index", https://doi.org/10.17617/3.EJQGAK, Edmond, V1
The repository contains files for a nearest neighbor index of text embeddings for the entire Pile dataset. For more information see: https://github.com/socialfoundations/tttlm |
May 19, 2023
Gürtler, Nico; Blaes, Sebastian; Kolev, Pavel; Widmaier, Felix; Wuthrich, Manuel; Bauer, Stefan; Schölkopf, Bernhard; Martius, Georg, 2023, "TriFinger RL Datasets", https://doi.org/10.17617/3.DXZ7TL, Edmond, V1
Offline reinforcement learning datasets collected on real TriFinger robots and with a simulated version of the robot. Trajectories for two dexterous manipulation tasks were collected: Pushing a cube to a goal position on the ground and Lifting it to a goal position and orientatio... |