Tools & Automation

CLI tools, utilities, converters, workflow automation, and productivity helpers

skills in category: 49,285
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Showing 17,689–17,712 of 49,285 skills

Bad And Good Errors Valueweighted Skill Scores In Deep Ensemble LearningA**arXiv ID:** 2103.02881 **Authors:** Sabrina Guastavino, Michele Piana, Federico Benvenuto **Published:** 2021-03-04T08:05:13Z **Abstract:** In this paper we propose a novel approach to realize forecast verification. Specifically, we introduce a strategy for assessing the severity of forecast errors based on the evidence that, on the one hand, a false alarm just anticipating an occurring event is better than one in the middle of consecutive non-occurring events, and that, on the other hand, ...toolsgoperformanceVotes: 0GitHub stars: 3
Autotandemml Active Learning Enhanced Tandem Neural Networks For Inverse Design ProblemsA**arXiv ID:** 2502.15643 **Authors:** Luka Grbcic, Juliane Müller, Wibe Albert de Jong **Published:** 2025-02-21T18:10:56Z **Abstract:** Inverse design in science and engineering involves determining optimal design parameters that achieve desired performance outcomes, a process often hindered by the complexity and high dimensionality of design spaces, leading to significant computational costs. To tackle this challenge, we propose a novel hybrid approach that combines active learning with Tan...toolsperformanceVotes: 0GitHub stars: 3
Autonomous Learning And Chaining Of Motor Primitives Using The Free Energy PrincipleA**arXiv ID:** 2005.05151 **Authors:** Louis Annabi, Alexandre Pitti, Mathias Quoy **Published:** 2020-05-11T14:43:55Z **Abstract:** In this article, we apply the Free-Energy Principle to the question of motor primitives learning. An echo-state network is used to generate motor trajectories. We combine this network with a perception module and a controller that can influence its dynamics. This new compound network permits the autonomous learning of a repertoire of motor trajectories. To evalua...toolsVotes: 0GitHub stars: 3
Automating Rigid Origami DesignA**arXiv ID:** 2211.13219 **Authors:** Jeremia Geiger, Karolis Martinkus, Oliver Richter, Roger Wattenhofer **Published:** 2022-11-20T17:13:50Z **Abstract:** Rigid origami has shown potential in large diversity of practical applications. However, current rigid origami crease pattern design mostly relies on known tessellations. This strongly limits the diversity and novelty of patterns that can be created. In this work, we build upon the recently developed principle of three units method to for...toolsVotes: 0GitHub stars: 3
Automatic Pattern Classification By Unsupervised Learning Using Dimensionality Reduction Of Data With Mirroring Neural NetworksA**arXiv ID:** 0712.0938 **Authors:** Dasika Ratna Deepthi, G. R. Aditya Krishna, K. Eswaran **Published:** 2007-12-06T13:52:04Z **Abstract:** This paper proposes an unsupervised learning technique by using Multi-layer Mirroring Neural Network and Forgy's clustering algorithm. Multi-layer Mirroring Neural Network is a neural network that can be trained with generalized data inputs (different categories of image patterns) to perform non-linear dimensionality reduction and the resultant low-dime...toolsgoVotes: 0GitHub stars: 3
Arxiv Safe AccessABest practices for safely accessing arXiv programmatically, avoiding common pitfalls with HTTP, SSL, and automated tools.toolspythongoVotes: 0GitHub stars: 3
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Arxiv 2609 10518v1 Braintaskonomy Learning How To Pretrain And What TA**arXiv ID:** 2609.10518v1 **Authors:** Junfeng Xia, Wenhao Ye, Junxiang Zhang, Jiayu Zuo, Mo Wang, Quanying Liu **URL:** http://arxiv.org/abs/2609.10518v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10494v1 Ibib A Protocol For Measuring Enterprise Ai SystemA**arXiv ID:** 2609.10494v1 **Authors:** Blake Stenstrom, Charangan Vasantharajan, Brian Sathianathan **URL:** http://arxiv.org/abs/2609.10494v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10490v1 Learning With Covariance Matrices Principal ComponA**arXiv ID:** 2609.10490v1 **Authors:** Saurabh Sihag, Andrea Cavallo, Elvin Isufi, Gonzalo Mateos, Alejandro Ribeiro **URL:** http://arxiv.org/abs/2609.10490v1 **Utility Score:** 1.00toolsgoVotes: 0GitHub stars: 3
Arxiv 2609 10487v1 Nonmaximal Sums Of Maximally Monotone Operators UnA**arXiv ID:** 2609.10487v1 **Authors:** Weifeng Yang **URL:** http://arxiv.org/abs/2609.10487v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10464v1 Semigroup Jepa Latent Dynamics Consistency For ZerA**arXiv ID:** 2609.10464v1 **Authors:** Andy Zeyi Liu, Haoran Sun, Lucas Baker, Randall Balestriero, John Sous **URL:** http://arxiv.org/abs/2609.10464v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10451v1 Jarvisgui Towards Cross Device Gui Agents With DynA**arXiv ID:** 2609.10451v1 **Authors:** Zixiang Chen, Yuheng Lu, Zihao Cheng, Zeming Liu, Jizeng Bai, Ziye Huang, Zhiyin Lin, Zihan Li, Yuhang Guo, Yunhong Wang, Haifeng Wang **URL:** http://arxiv.org/abs/2609.10451v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
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Arxiv 2609 10441v1 Convmem Convolutional Memory For Long Context ReasA**arXiv ID:** 2609.10441v1 **Authors:** Hongming Zhang, Zhaozhen Gu, Fengshuo Bai, Ming Hao, Qingyang Zhang, Yuanyuan Wang, Shiyang Tang, Yanna Wang, Bo Xu **URL:** http://arxiv.org/abs/2609.10441v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10439v1 Forgetting Only What Matters Layer Selective UnleaA**arXiv ID:** 2609.10439v1 **Authors:** Ravi Ranjan, Olivera Kotevska, Agoritsa Polyzou **URL:** http://arxiv.org/abs/2609.10439v1 **Utility Score:** 1.00toolsgoVotes: 0GitHub stars: 3
Arxiv 2609 10428v1 Algorithmic Stability Via EnsemblingA**arXiv ID:** 2609.10428v1 **Authors:** Rina Foygel Barber, Richard J. Samworth **URL:** http://arxiv.org/abs/2609.10428v1 **Utility Score:** 1.00toolsgoVotes: 0GitHub stars: 3
Arxiv 2609 10421v1 Emergency Department Revisit Quality Review ScreenA**arXiv ID:** 2609.10421v1 **Authors:** Jonathan A. Handler, Marlene I. Robles-Granda, Jacob E. Mefford, Jeremy S. McGarvey, Gregory S. Podolej, Colleen J. Klein, Matthew D. Dalstrom, William F. Bond **URL:** http://arxiv.org/abs/2609.10421v1 **Utility Score:** 1.00toolsgoVotes: 0GitHub stars: 3
Arxiv 2609 10410v1 Can Foundation Models Moderate Online Content EvalA**arXiv ID:** 2609.10410v1 **Authors:** Ayan Majumdar, Shounak Paul, Pushpdeep Singh, Ines Abdelaziz, Sayeh Jarollahi, Seungeon Lee, Krishna P. Gummadi, Ingmar Weber, Abhisek Dash **URL:** http://arxiv.org/abs/2609.10410v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10404v1 Hybridflow Sdn Orchestrated Client Partitioning FoA**arXiv ID:** 2609.10404v1 **Authors:** Osama Abu Hamdan, Rabin Pandey, Hao Che, Engin Arslan, Md Arifuzzaman **URL:** http://arxiv.org/abs/2609.10404v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
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Arxiv 2609 10385v1 Moonwalk Mediating Operations With Intent EvidenceA**arXiv ID:** 2609.10385v1 **Authors:** Shih-Yu Lai, Wen-Fan Wang, Sai Ling, Shaune Jan, Bing-Yu Chen, Xiang Anthony Chen **URL:** http://arxiv.org/abs/2609.10385v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10372v1 Pace Perceived Latency Aware Cascading Service RouA**arXiv ID:** 2609.10372v1 **Authors:** Lin Huang, Yujuan Tan, Weisheng Li, Lixiang Zeng, Kun Yang, Suihan Xiao **URL:** http://arxiv.org/abs/2609.10372v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10357v1 A Later Test Set Is Not A New Domain Pretraining FA**arXiv ID:** 2609.10357v1 **Authors:** Mahdi Naser Moghadasi, Faezeh Ghaderi **URL:** http://arxiv.org/abs/2609.10357v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10346v1 Beyond One Size Fits All Sample Adaptive StrategyA**arXiv ID:** 2609.10346v1 **Authors:** Haiji Liang, Pengfei Zhou, Zhenglin Wan, Wei Wang, Yang You, Wangbo Zhao **URL:** http://arxiv.org/abs/2609.10346v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10335v1 From Symbolic Perception To Logical Deduction A FrA**arXiv ID:** 2609.10335v1 **Authors:** Weichen Dai, Rafael Medeiros Cabral, Ziyi Shou, Yan Cao, Xin Shen, Dongcai Lu, Yi Zhou **URL:** http://arxiv.org/abs/2609.10335v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3
Arxiv 2609 10307v1 View Structured Conformal Prediction For 3d GaussiA**arXiv ID:** 2609.10307v1 **Authors:** Junzheng Chu, Bin Pan, Zhenwei Shi **URL:** http://arxiv.org/abs/2609.10307v1 **Utility Score:** 1.00toolsVotes: 0GitHub stars: 3