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Papers matching “scalable learning” 40

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Learning Lifted STRIPS Models from Action Traces Alone: A Simple, General, and Scalable Solution
2024 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Jonas Gösgens, Héctor Geffner

0

citations
Scalable Gaussian Process Regression via Deterministic Trigonometric Features: Uniform Bounds for Safe Model Predictive Control
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Julius Jagdt, Johanna Menn, Sebastian Trimpe, Melanie N. Zeilinger, Anna Scampicchio

0

citations
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems
2022 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Dominik Baumann

0

citations
EconoJax: A Fast & Scalable Economic Simulation in Jax
2024 RePEc: Research Papers in Economics preprint Computer Science Reinforcement Learning in Robotics Open access

Koen Ponse, Aske Plaat, Bas van Stein, Thomas M. Moerland

0

citations
Learning Sketch Decompositions in Planning via Deep Reinforcement Learning
2024 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Michael Aichmüller, Héctor Geffner

0

citations
Quantum Deep Learning: A Comprehensive Review
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Yanjun Ji, Zhao-Yun Chen, Marco Roth, David A. Kreplin, Christian Schiffer, Martin King, +7 more

0

citations
SEVERE++: Evaluating Benchmark Sensitivity in Generalization of Video Representation Learning
2025 arXiv (Cornell University) preprint Computer Science Human Pose and Action Recognition Open access

Fida Mohammad Thoker, Letian Jiang, Chen Zhao, Piyush Bagad, Hazel Doughty, Bernard Ghanem, +1 more

0

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Quantum Deep Learning: A Comprehensive Review
2026 JuSER (Forschungszentrum Jülich) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Yanjun Ji, Zhao-Yun Chen, Marco Roth, David A. Kreplin, Christian Schiffer, Martin King, +7 more

0

citations
Symmetry-invariant quantum machine learning force fields
2023 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher, Ivano Tavernelli, Francesco Tacchino

4

citations
Learning Explainable and Better Performing Representations of POMDP Strategies
2024 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Alexander Bork, Debraj Chakraborty, Kush Grover, Jan Křetínský, Stefanie Mohr

2

citations
Extraction of Quantitative Specimen Data using Machine Learning as a Service in the DiSSCo Research Infrastructure
2025 preprint Computer Science Advanced Neural Network Applications Open access

Claus Weiland, Jonas Grieb, Soulaine Theocharides, Sam Leeflang, Wouter Addink, Sharif Islam

1

citations
Application of the learning from errors principle in tufting machines
2025 arXiv (Cornell University) preprint Computer Science Augmented Reality Applications Open access

LONGXIANG SHAO, Dominik Hüsener, Michael Schluse, Juergen Rossmann

0

citations
Application of the learning from errors principle in tufting machines
2025 arXiv (Cornell University) preprint Computer Science Augmented Reality Applications Open access

LONGXIANG SHAO, Dominik Hüsener, Michael Schluse, Juergen Rossmann

0

citations
Accurately Solving Physical Systems with Graph Learning
2020 arXiv (Cornell University) preprint Computer Science Computer Graphics and Visualization Techniques Open access

Tassilo Kugelstadt, Wojtek Pałubicki, Jan Bender, Sören Pirk, Dominik Ludewig Michels

4

citations
BanffNET, a Deep Learning System for Comprehensive Histological Lesion Quantification in Kidney Transplant Biopsies
2026 medRxiv preprint Computer Science AI in cancer detection Open access

Giorgio Buzzanca, Chiara Pala, Junling He, Rianne Hofstraat, Alessandra Tammaro, Dominique van Midden, +41 more

2

citations
Graph Learning with 1D Convolutions on Random Walks.
2021 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Jan Toenshoff, Martin Ritzert, Hinrikus Wolf, Martin Grohe

5

citations
A Full Compression Pipeline for Green Federated Learning in Communication-Constrained Environments
2026 arXiv (Cornell University) preprint Computer Science Privacy-Preserving Technologies in Data Open access

Elouan Colybes, Shirin Salehi, Anke Schmeink

0

citations
Deep Learning of Causal Structures in High Dimensions
2022 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee

0

citations
Scalable and interpretable quantum natural language processing: an implementation on trapped ions
2024 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Tiffany Duneau, Gabriel Matos, Tuomas Laakkonen, Katerina Saiti, Anna Pearson, Konstantinos Meichanetzidis, +1 more

0

citations
Scalable Concept Extraction in Industry 4.0
2023 arXiv (Cornell University) preprint Computer Science Explainable Artificial Intelligence (XAI) Open access

Andrés Felipe Posada-Moreno, Florian Brillowski, Friedrich Solowjow, Thomas Gries

0

citations
Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Bernd Frauenknecht, Lukas Kesper, Daniel Mayfrank, Henrik Hose, Sebastian Trimpe

0

citations
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Anke Schmeink

0

citations
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Anke Schmeink

0

citations