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Papers matching “probability sampling” 19

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On Sampling-Based Training Criteria for Neural Language Modeling
2021 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Yingbo Gao, David Thulke, Alexander Gerstenberger, Ralf Schlüter, Hermann Ney

0

citations
Self-Normalized Importance Sampling for Neural Language Modeling
2021 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Zijian Yang, Yingbo Gao, Alexander Gerstenberger, Jintao Jiang, Ralf Schlüter, Hermann Ney

0

citations
Efficient Sparsification of Simplicial Complexes via Local Densities of States
2025 arXiv (Cornell University) preprint Computer Science Topological and Geometric Data Analysis Open access

Anton Savostianov, Michael T. Schaub, Nicola Guglielmi, Francesco Tudisco

0

citations
Random Abstract Cell Complexes
2024 arXiv (Cornell University) preprint Computer Science Topological and Geometric Data Analysis Open access

Josef Hoppe, Michael T. Schaub

0

citations
Tabu-driven Quantum Neighborhood Samplers
2020 Leiden Repository (Leiden University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

3

citations
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Jörn Tebbe, Christoph Zimmer, Ansgar Steland, Markus Lange‐Hegermann, Fabian Mies

0

citations
Exposing Finite-Depth, Finite-Shot Guarantees for Constrained Quantum Optimization via Fejér Filtering
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Chinonso Onah, Kristel F. L. Michielsen

0

citations
Robust Shielding for Safe Reinforcement Learning
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Edwin Hamel-De le Court, Thom Badings, Alessandro Abate, Francesco Belardinelli, Francesco Fabiano

0

citations
Ordered Subgraph Aggregation Networks
2022 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert

8

citations
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
2023 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Semih Çaycı, Atilla Eryılmaz

2

citations
Unconsciously Forget: Mitigating Memorization; Without Knowing What is being Memorized
2025 arXiv (Cornell University) preprint Computer Science Generative Adversarial Networks and Image Synthesis Open access

Yang Zhang, Yongli Mou, Yanfei Dong, Stefan Decker, Kenji Kawaguchi, Johannes Stegmaier

0

citations
Polynomial Time Quantum Approximation Schemes for Constrained Optimisation
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Chinonso Onah, Kristel F. L. Michielsen

0

citations
Separating Geometry From Interference in Constrained Quantum Optimization
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Chinonso Onah, Stuart Hadfield, Kristel F. L. Michielsen

0

citations
Rigorous methods for computational number theory
2025 arXiv (Cornell University) preprint Computer Science Cryptography and Residue Arithmetic Open access

0

citations
Upside Down Reinforcement Learning with Policy Generators
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Dylan R. Ashley, Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber

0

citations
One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Juan Agustin Duque, Sergio García Heredia, Vinicius Hernandes, Eliška Greplová, Thomas Spriggs, Aaron Courville, +1 more

0

citations
Provable learning separation for predicting time-evolution of quantum many-body systems
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Rahul Bandyopadhyay, Riccardo Molteni, Jens Eisert, Vedran Dunjko, Sofiène Jerbi

0

citations
Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machines
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Kevin Shen, Susanne Pielawa, Vedran Dunjko, Hao Wang

0

citations
Preference-Based Reward Learning under Partial Observability with Inexact Dynamics
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Reza Zolnouri, Semih Çaycı

0

citations

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