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Claude Skills by hiyenwong
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- Arxiv 2609 03829v1 The Impact Of Phase Information For Few Shot Fine**arXiv ID:** 2609.03829v1 **Authors:** Ruiling Liu, Linyue Zhang, Wenyi Zeng, Jiamiao Lu, Weichuang Zhang, Changming Sun, Zejun Zhang, Xiao Zhao **URL:** http://arxiv.org/abs/2609.03829v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 03858v1 High Dimensional Learning Dynamics Of Attention In**arXiv ID:** 2609.03858v1 **Authors:** Yizhou Xu, Margarita Sagitova, Lenka Zdeborová, Florent Krzakala **URL:** http://arxiv.org/abs/2609.03858v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 04105v1 Hardware Aware Fp4 Flashattention 4**arXiv ID:** 2609.04105v1 **Authors:** Robert Hu **URL:** http://arxiv.org/abs/2609.04105v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 04172v1 Rethinking On Policy Distillation Of Large Languag**arXiv ID:** 2609.04172v1 **Authors:** Zixuan Fu, Bingxiang He, Yuxin Zuo, Haohuan Huang, Jinqian Zhang, Ruhang Xiao, Cheng Qian, Qinyu Luo, Huan-ang Gao, Yudong Wang, Zhiyuan Liu, Ning Ding, Chaojun Xiao **URL:** http://arxiv.org/abs/2609.04172v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 07355v1 Determinants Of Hyperparameter Robustness In Conne**arXiv ID:** 2609.07355v1 **Authors:** Miles Walter Churchland, Raul de Palma Aristides, Jordi Garcia-Ojalvo, Anna Ritz, Greg Anderson, Miguel C. Soriano **URL:** http://arxiv.org/abs/2609.07355v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08312v1 Non Coherent Over The Air Federated Learning Proto**arXiv ID:** 2609.08312v1 **Authors:** Haifeng Wen, Nicolò Michelusi, Osvaldo Simeone, Yang Yang, Hong Xing **URL:** http://arxiv.org/abs/2609.08312v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08318v1 Attncompress Dynamic Attention Guided Trajectory C**arXiv ID:** 2609.08318v1 **Authors:** Zhengran Zeng, Yixin Li, Rui Xie, Wei Ye, Shikun Zhang **URL:** http://arxiv.org/abs/2609.08318v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08337v1 Distillation As Probability Transport Routed On Po**arXiv ID:** 2609.08337v1 **Authors:** Tianle Xia, Lingxiang Hu, Yiding Sun, Linfang Shang, Ming Xu, Lan Xu, Ning Zheng, Wei Xu, Jie Jiang **URL:** http://arxiv.org/abs/2609.08337v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08380v1 How To Make The Gradient Mapping Small For Constra**arXiv ID:** 2609.08380v1 **Authors:** Ahmet Alacaoglu **URL:** http://arxiv.org/abs/2609.08380v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08574v1 Do New Attention Mechanisms Actually Fix Attention**arXiv ID:** 2609.08574v1 **Authors:** Sara Rizwan, Samaanah Abdus Salam **URL:** http://arxiv.org/abs/2609.08574v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08615v1 Why Shared Attention Vectors Fail A Case For Outco**arXiv ID:** 2609.08615v1 **Authors:** Lenard Dome **URL:** http://arxiv.org/abs/2609.08615v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08638v1 Casd Chunk Aligned Semantic Distillation For Multi**arXiv ID:** 2609.08638v1 **Authors:** Tinghe Ding, Jiahao Li, He Wang **URL:** http://arxiv.org/abs/2609.08638v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08673v1 Bifta Brain Inspired Few Shot Tactile Adaptation F**arXiv ID:** 2609.08673v1 **Authors:** Boheng Liu, Ziyu Li, Xia Wu **URL:** http://arxiv.org/abs/2609.08673v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08683v1 Neither Adversarial Training Nor Purification Emer**arXiv ID:** 2609.08683v1 **Authors:** Mohammed-Yassine Habibi, Klea Ziu, Martin Takáč, Makoto Yamada **URL:** http://arxiv.org/abs/2609.08683v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08690v1 Hyperparameter Scaling Laws Across Moe Sparsity**arXiv ID:** 2609.08690v1 **Authors:** Changxin Tian, Kunlong Chen, Jia Liu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou **URL:** http://arxiv.org/abs/2609.08690v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08788v1 Adaptive Anisotropic Attention For Axis Structured**arXiv ID:** 2609.08788v1 **Authors:** Mahir Jain, Parshva Runwal, Aditya Ray Mishra, Arvasu Kulkarni, Sandeep Singh, Siddharth Panwar **URL:** http://arxiv.org/abs/2609.08788v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08901v1 The Batchnorm Illusion Diagnosing Normalization Ar**arXiv ID:** 2609.08901v1 **Authors:** Aaryaman Kalani, Murari Mandal, Dhruv Kumar, Mohan Kankanhalli, Yash Sinha **URL:** http://arxiv.org/abs/2609.08901v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08966v1 Good Pretraining Bad Sft Checkpoint Quality Across**arXiv ID:** 2609.08966v1 **Authors:** Sohir Maskey, Philipp Scholl, Jonas Knupp, Pit Neitemeier, Sascha Wirges **URL:** http://arxiv.org/abs/2609.08966v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08992v1 Physics Informed Deep Learning For False Ventricul**arXiv ID:** 2609.08992v1 **Authors:** Athanasios Papastathopoulos-Katsaros, Alexandra Stavrianidi, Zhandong Liu **URL:** http://arxiv.org/abs/2609.08992v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09099v1 Curriculum Learning As Transport Understanding Cur**arXiv ID:** 2609.09099v1 **Authors:** Changho Shin, David Alvarez-Melis **URL:** http://arxiv.org/abs/2609.09099v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09152v1 Silver Rate Is Almost Optimal For Gradient Descent**arXiv ID:** 2609.09152v1 **Authors:** Yuhan Ye, Kaizhao Liu **URL:** http://arxiv.org/abs/2609.09152v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09591v1 Modality Decoupled Federated Learning For Privacy**arXiv ID:** 2609.09591v1 **Authors:** Zhuodong Liu, Xiangyu Li, Chunhong Yuan, Hongyang Du, Bodong Shang, Qingqing Wu, Tony Q. S. Quek, Mohsen Guizani **URL:** http://arxiv.org/abs/2609.09591v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09659v1 Cascading Gradient Inversion Via Lt Code Inspired**arXiv ID:** 2609.09659v1 **Authors:** Saeed Shariati, Mohsen Alambardar Meybodi **URL:** http://arxiv.org/abs/2609.09659v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09708v1 Efficient Graph Neural Networks For Multicarrier W**arXiv ID:** 2609.09708v1 **Authors:** Beier Li, Mai Vu **URL:** http://arxiv.org/abs/2609.09708v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09891v1 Prometa Few Shot Protac Targeted Degradation Predi**arXiv ID:** 2609.09891v1 **Authors:** Yuansheng Liu, Yufei Ye, Tao Tang, Jiawei Luo, Wen Tao, Xiao Luo **URL:** http://arxiv.org/abs/2609.09891v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09904v1 Beyond Conventional Federated Learning Via High Or**arXiv ID:** 2609.09904v1 **Authors:** Alireza Kabgani, Masoud Ahookhosh **URL:** http://arxiv.org/abs/2609.09904v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09925v1 Time Frequency Geometric Cross Attention For Chunk**arXiv ID:** 2609.09925v1 **Authors:** Shengye Dong, Haochen Niu, Hao Liu, Peiwen Lin, Chuang Wang, Shanmin Pang **URL:** http://arxiv.org/abs/2609.09925v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09945v1 Adversarial Training For Tabular Credit Scoring A**arXiv ID:** 2609.09945v1 **Authors:** Gijs A. F. Niewzwaag, Marijn G. S. Veth, Manuele Massei, Marcos R. Machado **URL:** http://arxiv.org/abs/2609.09945v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09971v1 Deep Neural Networks For Learning Intent From Semg**arXiv ID:** 2609.09971v1 **Authors:** Zakariyya Brewster, Divy Wadhwani, Emily Yan, Aidan Wang, Karma Namgyal, Shuting Xie, Markiyan Konyk, Tala Abdelmaguid **URL:** http://arxiv.org/abs/2609.09971v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10012v1 An Explainable Machine Learning Framework For Pred**arXiv ID:** 2609.10012v1 **Authors:** Fatemeh Mahmoudi **URL:** http://arxiv.org/abs/2609.10012v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10026v1 Beyond Contact Sensors Deep Learning With Pseudo L**arXiv ID:** 2609.10026v1 **Authors:** Bhargav Acharya, Barbara Hammer, Hanna Drimalla **URL:** http://arxiv.org/abs/2609.10026v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10051v1 Zero Shot Temporal Localisation Of Audio Deepfakes**arXiv ID:** 2609.10051v1 **Authors:** Soumyadeep Roy **URL:** http://arxiv.org/abs/2609.10051v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10084v1 A Statistical Approach To Bias In Zero Shot Learni**arXiv ID:** 2609.10084v1 **Authors:** Clarence Chew, Gim Siang Chia, Sukalpa Chanda, Subhroshekhar Ghosh, Soumendu Sundar Mukherjee **URL:** http://arxiv.org/abs/2609.10084v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10092v1 Rap Research Attention Prediction Reveals Target C**arXiv ID:** 2609.10092v1 **Authors:** Yingqian Wu, Jingcong Liang, Siyuan Wang, Zhenfei Yin, Philip Torr, Junchi Yu, Zhongyu Wei **URL:** http://arxiv.org/abs/2609.10092v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10108v1 A Trust Network Based Federated Learning Framework**arXiv ID:** 2609.10108v1 **Authors:** Chunxu Zhang, Bo Li, Wenliang Wang, Yang Liu, Di Jiang, Yuan Huang, Yo-ichi Nabeshima, Akinori Yamamura, Bo Yang, Qiang Yang **URL:** http://arxiv.org/abs/2609.10108v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10154v1 Compassopd Cross Family On Policy Distillation Via**arXiv ID:** 2609.10154v1 **Authors:** Naibin Gu, Qingyi Si, Chenxu Yang, Chuanyu Qin, Junhao Zhou, Peng Fu, Zheng Lin, Weiping Wang **URL:** http://arxiv.org/abs/2609.10154v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10177v1 Beyond Surface Imitation Contrastive Modeling For**arXiv ID:** 2609.10177v1 **Authors:** Mingbo Yang, Wenqiang Wang, Zhaolu Kang, Peng Chen, Yannan Chen, Sunshang Wang, Yan Xiao **URL:** http://arxiv.org/abs/2609.10177v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10183v1 A Bio Plausible Visual Neural Network For Locust I**arXiv ID:** 2609.10183v1 **Authors:** Qinbing Fu, Jiani Li, Jiajun Huang, Jigen Peng **URL:** http://arxiv.org/abs/2609.10183v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10299v1 A Dominant Diffuse Phase In The Sparse Autoencoder**arXiv ID:** 2609.10299v1 **Authors:** Alexis D. Plascencia **URL:** http://arxiv.org/abs/2609.10299v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10311v1 One Loop Two Gains Can Active Learning Win The Lot**arXiv ID:** 2609.10311v1 **Authors:** Benedikt Tscheschner, Eduardo Veas, Marc Masana **URL:** http://arxiv.org/abs/2609.10311v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10364v1 Omnimed Fl A Robust Multimodal Federated Learning**arXiv ID:** 2609.10364v1 **Authors:** Ayush Debnath, Ruelia Saha, Sudip Misra **URL:** http://arxiv.org/abs/2609.10364v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10479v1 Deep Learning Based Detection Of Electrical Faults**arXiv ID:** 2609.10479v1 **Authors:** Ian C. Guzmán, Radu Babiceanu, Berker Peköz **URL:** http://arxiv.org/abs/2609.10479v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10534v1 Likelihood Free Inference With Nuisance Parameters**arXiv ID:** 2609.10534v1 **Authors:** Phil Assheton **URL:** http://arxiv.org/abs/2609.10534v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Assessing The Generalizability Of A Performance Predictive Model**arXiv ID:** 2306.00040 **Authors:** Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov **Published:** 2023-05-31T12:50:44Z **Abstract:** A key component of automated algorithm selection and configuration, which in most cases are performed using supervised machine learning (ML) methods is a good-performing predictive model. The predictive model uses the feature representation of a set ...Votes: 0GitHub stars: 3
- Attend And Predict Understanding Gene Regulation By Selective Attention On Chromatin**arXiv ID:** 1708.00339 **Authors:** Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi **Published:** 2017-08-01T14:06:12Z **Abstract:** The past decade has seen a revolution in genomic technologies that enable a flood of genome-wide profiling of chromatin marks. Recent literature tried to understand gene regulation by predicting gene expression from large-scale chromatin measurements. Two fundamental challenges exist for such learning tasks: (1) genome-wide chromatin signals are...Votes: 0GitHub stars: 3
- Autoencoding With A Classifier System**arXiv ID:** 1910.10579 **Authors:** Richard J. Preen, Stewart W. Wilson, Larry Bull **Published:** 2019-10-23T14:27:29Z **Abstract:** Autoencoders are data-specific compression algorithms learned automatically from examples. The predominant approach has been to construct single large global models that cover the domain. However, training and evaluating models of increasing size comes at the price of additional time and computational cost. Conditional computation, sparsity, and model pruning...Votes: 0GitHub stars: 3
- Automated Deep Learning For Load Forecasting**arXiv ID:** 2405.08842 **Authors:** Julie Keisler, Sandra Claudel, Gilles Cabriel, Margaux Brégère **Published:** 2024-05-14T07:51:55Z **Abstract:** Accurate forecasting of electricity consumption is essential to ensure the performance and stability of the grid, especially as the use of renewable energy increases. Forecasting electricity is challenging because it depends on many external factors, such as weather and calendar variables. While regression-based models are currently effective, ...Votes: 0GitHub stars: 3
- Automatic Gradient Descent Deep Learning Without Hyperparameters**arXiv ID:** 2304.05187 **Authors:** Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue **Published:** 2023-04-11T12:45:52Z **Abstract:** The architecture of a deep neural network is defined explicitly in terms of the number of layers, the width of each layer and the general network topology. Existing optimisation frameworks neglect this information in favour of implicit architectural information (e.g. second-order methods) or architecture-agnostic distance functions (e.g...Votes: 0GitHub stars: 3
- Automatically Detecting Anomalous Exoplanet Transits**arXiv ID:** 2111.08679 **Authors:** Christoph J. Hönes, Benjamin Kurt Miller, Ana M. Heras, Bernard H. Foing **Published:** 2021-11-16T18:24:49Z **Abstract:** Raw light curve data from exoplanet transits is too complex to naively apply traditional outlier detection methods. We propose an architecture which estimates a latent representation of both the main transit and residual deviations with a pair of variational autoencoders. We show, using two fabricated datasets, that our latent represe...Votes: 0GitHub stars: 3
- Bacterial Reservoir ComputingBacterial metabolic models as physical reservoirs for computation. dFBA simulations of microbial growth curves as reservoir states. Separability and similarity metrics predict performance. Activation: reservoir computing, bacterial model, biological computation, dFBA.Votes: 0GitHub stars: 3