Fuentes de referencia

Referencias 145–168 de 766

145. Consistency Models

     Yang Song; Prafulla Dhariwal; Mark Chen; Ilya Sutskever
     2023
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     • One Step Is a Budget, Not a Distribution: Consistency Models and the Evidence for Fast Generation

146. Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

     Dongjun Kim; Chieh-Hsin Lai; Wei-Hsiang Liao; Naoki Murata; Yuhta Takida; Toshimitsu Uesaka; Yutong He; Yuki Mitsufuji; Stefano Ermon
     2024
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     • One Step Is a Budget, Not a Distribution: Consistency Models and the Evidence for Fast Generation

147. Constants Count: Practical Improvements to Oblivious RAM

     Ling Ren; Christopher W. Fletcher; Albert Kwon; Emil Stefanov; Elaine Shi; Marten van Dijk; Srinivas Devadas
     2014
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     • Hiding the Address: Oblivious RAM, Leakage, and the Cost of Access Privacy

148. Continual Learning Through Synaptic Intelligence

     Friedemann Zenke; Ben Poole; Surya Ganguli
     2017
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     • What a Continual Learner Remembers: Replay, Constraints, and the Accounting of Forgetting

149. Continual learning with hypernetworks

     Johannes von Oswald; Christian Henning; Benjamin F. Grewe; João Sacramento
     2020
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     • Weights as Conditional Outputs: Hypernetworks, Modulation, and the Limits of Parameter Sharing

150. Continual Test-Time Domain Adaptation

     Qin Wang; Olga Fink; Luc Van Gool; Dengxin Dai
     2022
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     • When Inference Updates the Model: Test-Time Adaptation, Confidence, and State Drift

151. Continuous Query Optimization

     Ron Avnur; Joseph M. Hellerstein
     1999
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     • Query Plans under Uncertainty: Cardinality Error, Regret, and Robust Execution

152. Convolutional Neural Operators for robust and accurate learning of PDEs

     Bogdan Raonić; Roberto Molinaro; Tim De Ryck; Tobias Rohner; Francesca Bartolucci; Rima Alaifari; Siddhartha Mishra; Emmanuel de Bézenac
     2023
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     • Learning an Operator Across Grids: Resolution, Aliasing, and What Transfers

153. Cornucopia: Temporal Safety for CHERI Heaps

     Nathaniel Wesley Filardo; Brett F. Gutstein; Jonathan Woodruff; Sam Ainsworth; Lucian Paul-Trifu; Brooks Davis; Hongyan Xia; Edward Tomasz Napierala; Alexander Richardson; John Baldwin; David Chisnall; Jessica Clarke; Khilan Gudka; Alexandre Joannou; A. Theodore Markettos; Alfredo Mazzinghi; Robert M. Norton; Michael Roe; Peter Sewell; Stacey Son; Timothy M. Jones; Simon W. Moore; Peter G. Neumann; Robert N. M. Watson
     2020
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     • Memory Safety with Capabilities: Spatial Authority, Lifetime, and Revocation

154. Covariate Shift Adaptation by Importance Weighted Cross Validation

     Masashi Sugiyama; Matthias Krauledat; Klaus-Robert Müller
     2007
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     • Generalization Under Shift Requires Identifiable Assumptions

155. CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks

     Ellen D. Zhong; Tristan Bepler; Bonnie Berger; Joseph H. Davis
     2021
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     • A Molecule in Motion from Still Images: Cryo-EM Heterogeneity and the Limits of Reconstruction

156. CUDA C++ Best Practices Guide

     NVIDIA
     2026
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     • Beyond Peak FLOPS: GPU Performance as a Sequence of Resource Constraints

157. Curriculum Learning

     Yoshua Bengio; Jérôme Louradour; Ronan Collobert; Jason Weston
     2009
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     • A Curriculum Is Also a Sampling Policy

158. CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features

     Sangdoo Yun; Dongyoon Han; Seong Joon Oh; Sanghyuk Chun; Junsuk Choe; Youngjoon Yoo
     2019
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     • Interpolation Changes the Learning Distribution

159. D4RL: Datasets for Deep Data-Driven Reinforcement Learning

     Justin Fu; Aviral Kumar; Ofir Nachum; George Tucker; Sergey Levine
     2021
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     • The Action Missing from the Dataset: Support, Pessimism, and Identification in Offline Deep Reinforcement Learning

160. Dapper, a Large-Scale Distributed Systems Tracing Infrastructure

     Benjamin H. Sigelman; Luiz André Barroso; Mike Burrows; Pat Stephenson; Manoj Plakal; Donald Beaver; Saul Jaspan; Chandan Shanbhag
     2010
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     • Seeing a Distributed Execution: Sampling, Context, and the Limits of Trace Evidence

161. Dark Experience for General Continual Learning: a Strong, Simple Baseline

     Pietro Buzzega; Matteo Boschini; Angelo Porrello; Davide Abati; Simone Calderara
     2020
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     • What a Continual Learner Remembers: Replay, Constraints, and the Accounting of Forgetting

162. Dark Matter Search Results from a One Ton-Year Exposure of XENON1T

     E. Aprile; J. Aalbers; F. Agostini; M. Alfonsi; L. Althueser; F. D. Amaro; M. Anthony; F. Arneodo; L. Baudis; B. Bauermeister; M. L. Benabderrahmane; T. Berger; P. A. Breur; A. Brown; A. Brown; E. Brown; S. Bruenner; G. Bruno; R. Budnik; C. Capelli; J. M. R. Cardoso; D. Cichon; D. Coderre; A. P. Colijn; J. Conrad; J. P. Cussonneau; M. P. Decowski; P. de Perio; P. Di Gangi; A. Di Giovanni; S. Diglio; A. Elykov; G. Eurin; J. Fei; A. D. Ferella; A. Fieguth; W. Fulgione; A. Gallo Rosso; M. Galloway; F. Gao; M. Garbini; C. Geis; L. Grandi; Z. Greene; H. Qiu; C. Hasterok; E. Hogenbirk; J. Howlett; R. Itay; F. Joerg; B. Kaminsky; S. Kazama; A. Kish; G. Koltman; H. Landsman; R. F. Lang; L. Levinson; Q. Lin; S. Lindemann; M. Lindner; F. Lombardi; J. A. M. Lopes; J. Mahlstedt; A. Manfredini; T. Marrodán Undagoitia; J. Masbou; D. Masson; M. Messina; K. Micheneau; K. Miller; A. Molinario; K. Morå; M. Murra; J. Naganoma; K. Ni; U. Oberlack; B. Pelssers; F. Piastra; J. Pienaar; V. Pizzella; G. Plante; R. Podviianiuk; N. Priel; D. Ramírez García; L. Rauch; S. Reichard; C. Reuter; B. Riedel; A. Rizzo; A. Rocchetti; N. Rupp; J. M. F. dos Santos; G. Sartorelli; M. Scheibelhut; S. Schindler; J. Schreiner; D. Schulte; M. Schumann; L. Scotto Lavina; M. Selvi; P. Shagin; E. Shockley; M. Silva; H. Simgen; D. Thers; F. Toschi; G. Trinchero; C. Tunnell; N. Upole; M. Vargas; O. Wack; H. Wang; Z. Wang; Y. Wei; C. Weinheimer; C. Wittweg; J. Wulf; J. Ye; Y. Zhang; T. Zhu; XENON Collaboration <a href="#n7">7</a>
     2018
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     • A Null Result with Structure: Exposure, Thresholds and Backgrounds in Dark-Matter Searches

163. Data center TCP (DCTCP)

     Mohammad Alizadeh; Albert Greenberg; David A. Maltz; Jitendra Padhye; Parveen Patel; Balaji Prabhakar; Sudipta Sengupta; Murari Sridharan
     2010
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     • Congestion Control as Delayed Inference: Throughput, Queues, and Fairness

164. Data-dependent PAC-Bayes priors via differential privacy

     Gintare Karolina Dziugaite; Daniel M. Roy
     2018
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     • Who Chose the Prior? PAC-Bayes Certificates, Data Dependence, and the Cost of Selection

165. Data-Dependent Stability of Stochastic Gradient Descent

     Ilja Kuzborskij; Christoph H. Lampert
     2018
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     • What One Replaced Example Changes: Algorithmic Stability, Training Time, and Generalization

166. Data-driven discovery of partial differential equations

     Samuel H. Rudy; Steven L. Brunton; Joshua L. Proctor; J. Nathan Kutz
     2017
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     • Discovering an Equation from Data: Sparse Structure, Hidden Variables and Experimental Design

167. DataComp: In search of the next generation of multimodal datasets

     Samir Yitzhak Gadre; Gabriel Ilharco; Alex Fang; et al.
     2023
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     • Data Multiplicity Is a Training Measure

168. DBSP: Automatic Incremental View Maintenance for Rich Query Languages

     Mihai Budiu; Frank McSherry; Leonid Ryzhyk; Val Tannen
     2022
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     • Maintaining a Fixed Point: Datalog, Retractions, and Incremental State