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Claude Skills by hiyenwong
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- Arxiv 2608 26743v1 Graph Guided Selective Unlearning For Language Mod**arXiv ID:** 2608.26743v1 **Authors:** Waqas Khan, Tabinda Sarwar, Jingyue Cong, Xun Yi, Estrid He **URL:** http://arxiv.org/abs/2608.26743v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26748v1 Self Augmented Diffusion Guidance For Physics Info**arXiv ID:** 2608.26748v1 **Authors:** Akira Osaka, Naoya Takeishi, Takehisa Yairi **URL:** http://arxiv.org/abs/2608.26748v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26848v1 Medfg Vqa Low Frequency Memory And Graph Attention**arXiv ID:** 2608.26848v1 **Authors:** Haowen Gu, Gensheng Pei, Zeren Sun, Mingwu Ren, Xiangbo Shu, Yazhou Yao, Fumin Shen **URL:** http://arxiv.org/abs/2608.26848v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26901v1 Dose Plannet Physics Based Radiotherapy Dose Predi**arXiv ID:** 2608.26901v1 **Authors:** Ankit Bhattacharjee, Sougata Maity, Santam Chakraborty, Indranil Mallick **URL:** http://arxiv.org/abs/2608.26901v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26961v1 Gromov Monge Flow Matching For Equivariant Graph G**arXiv ID:** 2608.26961v1 **Authors:** Moritz Piening, Christian Wald **URL:** http://arxiv.org/abs/2608.26961v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 27153v1 Inductive Correlation Clustering With Graph Neural**arXiv ID:** 2608.27153v1 **Authors:** Francesco Paolo Nerini, Francesco Bonchi, Arijit Khan, André Panisson **URL:** http://arxiv.org/abs/2608.27153v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30231v1 More Is Different In Neural Circuits Algebraic Eme**arXiv ID:** 2608.30231v1 **Authors:** Nima Dehghani **URL:** http://arxiv.org/abs/2608.30231v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30472v1 Toxlens A Reproducible Graph Learning Framework Fo**arXiv ID:** 2608.30472v1 **Authors:** Magnus H. Strømme, Alex G. C. de Sá, David B. Ascher **URL:** http://arxiv.org/abs/2608.30472v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30646v1 Big Sure Bipartite Graph For Semantic Uncertainty**arXiv ID:** 2608.30646v1 **Authors:** Debarpan Bhattacharya, Malay Phadke, Sriram Ganapathy **URL:** http://arxiv.org/abs/2608.30646v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30650v1 Geometry Of Divergence Tracking Hidden State Traje**arXiv ID:** 2608.30650v1 **Authors:** Jie Liang, Zhengxin Yu, Hamid Nasiri, Peter Garraghan **URL:** http://arxiv.org/abs/2608.30650v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30811v1 Topocompress Long Context Compression Via Graph Wi**arXiv ID:** 2608.30811v1 **Authors:** Daniel Agyei Asante, Yang Li **URL:** http://arxiv.org/abs/2608.30811v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30869v1 Exponential Random Graph Models With Soft Clique C**arXiv ID:** 2608.30869v1 **Authors:** Yasmin Tousinejad, Vera Koponen **URL:** http://arxiv.org/abs/2608.30869v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 31028v1 Learning The Geometry Of Admissible Hypotheses Thr**arXiv ID:** 2608.31028v1 **Authors:** James Crowley, Faez Ahmed, Anton van Beek **URL:** http://arxiv.org/abs/2608.31028v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02282v1 Routegraph Mona Confusion Aware Routing Fine Tunin**arXiv ID:** 2609.02282v1 **Authors:** Jierui Li, Zhiyuan Qi, Hao Zhu, Yufan Liu, Jixian Liu, Shaojie Jiang, Jianda Wang, Yaqi Liu, Xiaotong Li, Wei Wang **URL:** http://arxiv.org/abs/2609.02282v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02286v1 From Topology Learning To Graph Generation A Unify**arXiv ID:** 2609.02286v1 **Authors:** Xiaowen Dong, Hoi-To Wai, Siheng Chen, Laura Toni, Dorina Thanou **URL:** http://arxiv.org/abs/2609.02286v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02373v1 Percolation Dynamics In Optimization Variance Casc**arXiv ID:** 2609.02373v1 **Authors:** Sai Niranjan Ramachandran, Suvrit Sra **URL:** http://arxiv.org/abs/2609.02373v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02404v1 Evidence For Shared Routing Geometry And Dynamics**arXiv ID:** 2609.02404v1 **Authors:** Kirill Labzin, Stepan Kulibaba, Artem Dzhalilov, Artem Gorokhov **URL:** http://arxiv.org/abs/2609.02404v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02519v1 Spectral Initialization And Scheduled Graph Smooth**arXiv ID:** 2609.02519v1 **Authors:** Md Abrar Jahin, Taufikur Rahman Fuad, Jay Pujara, Craig A. Knoblock **URL:** http://arxiv.org/abs/2609.02519v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02538v1 A Comparative Study Of Graph Representations For G**arXiv ID:** 2609.02538v1 **Authors:** Adrian Degenkolb, Qiong Huang, Benjamin Schäfer **URL:** http://arxiv.org/abs/2609.02538v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02766v1 Do Tabular Foundation Models Know Physics Contamin**arXiv ID:** 2609.02766v1 **Authors:** Wassim Tenachi, Yashar Hezaveh, Laurence Perreault Levasseur, Pierre-Luc Bacon **URL:** http://arxiv.org/abs/2609.02766v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02881v1 Graph Machine Towards Better Pretraining Via Edges**arXiv ID:** 2609.02881v1 **Authors:** Lintai Hou **URL:** http://arxiv.org/abs/2609.02881v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 03383v1 Tigpo Temporal Instance Graph Policy Optimization**arXiv ID:** 2609.03383v1 **Authors:** Jinwei Gan **URL:** http://arxiv.org/abs/2609.03383v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 03816v1 When Vision Meets Graphs A Survey On Graph Reasoni**arXiv ID:** 2609.03816v1 **Authors:** Xinjian Zhao, Wei Pang, Zhixuan Yu, Xiangru Jian, Xiaozhuang Song, Yaoyao Xu, Zhongkai Xue, Dingshuo Chen, Shu Wu, Philip Torr, Tianshu Yu **URL:** http://arxiv.org/abs/2609.03816v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 04005v1 The Dually Flat Geometry Of Planning As Inference**arXiv ID:** 2609.04005v1 **Authors:** Nikola Milosevic, Asaki Kataoka, Nicolas Hinrichs, Kenji Doya, Nico Scherf **URL:** http://arxiv.org/abs/2609.04005v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08305v1 Fpicker Topology Guided Evolution For Filament Tra**arXiv ID:** 2609.08305v1 **Authors:** Tingyin Zhao, Mingtao Huang, Yuan Shen **URL:** http://arxiv.org/abs/2609.08305v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08476v1 When Topology Betrays Privacy Lattice Based Recons**arXiv ID:** 2609.08476v1 **Authors:** Wenrui Yu, Changlong Ji, Johannes Bjerva, Qiongxiu Li **URL:** http://arxiv.org/abs/2609.08476v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08594v1 Multi Level Set Based Physics Driven Neural Networ**arXiv ID:** 2609.08594v1 **Authors:** Yutong Du, Zicheng Liu, Bo Qi, Yali Zong, Peixian Han **URL:** http://arxiv.org/abs/2609.08594v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08709v1 Chimaera A Mixture Of Graph Experts Architecture F**arXiv ID:** 2609.08709v1 **Authors:** Jonathan Frank, David Richerby, Ansgar Scherp **URL:** http://arxiv.org/abs/2609.08709v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09135v1 Entropy Regularized Rank Masked Policy Optimizatio**arXiv ID:** 2609.09135v1 **Authors:** Jiacheng Xu, Feng Chen, Xiuneng Xu, Bo An **URL:** http://arxiv.org/abs/2609.09135v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09595v1 Teacher Geometry Shapes Learnability In Teacher St**arXiv ID:** 2609.09595v1 **Authors:** Kai J. Sandbrink, Flavio Martinelli, Alexander van Meegen, Wulfram Gerstner, Johanni Brea **URL:** http://arxiv.org/abs/2609.09595v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09626v1 Hyperbolic Geometry For Open World Object Detectio**arXiv ID:** 2609.09626v1 **Authors:** Wuzhou Li, Jiawei Zhou, Shenghang Wang, Xiang Li **URL:** http://arxiv.org/abs/2609.09626v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09912v1 Development And Validation Of A Physics Guided Mac**arXiv ID:** 2609.09912v1 **Authors:** Ashutosh Yadav, Alok Dubey, Prodyut Ranjan Chakraborty, Harshal Akolekar **URL:** http://arxiv.org/abs/2609.09912v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10077v1 Physics Informed Multi Task Surrogate Model For Th**arXiv ID:** 2609.10077v1 **Authors:** Sergey Nikiforov **URL:** http://arxiv.org/abs/2609.10077v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10529v1 A Positive Resolution Of The Gap Entropy Conjectur**arXiv ID:** 2609.10529v1 **Authors:** P. M. Aronow, Nathan Kallus, Patrick Lopatto **URL:** http://arxiv.org/abs/2609.10529v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Attack Detection Time Series Foundation ModelsModel-structure-free attack detection for cyber-physical systems using TimesFM time-series foundation model as surrogate residual generator. Zero-shot detection without plant model knowledge, handling both model-free replay attacks and model-based stealthy attacks. Foundation models as corrupted measurement substitutes when redundancy assumptions fail. Applications: CPS security, power systems, network attack detection. Activation: attack detection, cyber-physical security, TimesFM, foundatio...Votes: 0GitHub stars: 3
- Automated Entropy Inequality ProvingAutomated proving methodology for Shannon-type entropy inequalities using fine-tuned language models and guided tree search. Bridges information theory with AI for automated mathematical theorem discovery. Applicable to entropy inequality verification, information theory research, and automated theorem proving. arXiv: 2606.05729.Votes: 0GitHub stars: 3
- Automatic Synthesis Of Neurons For Recurrent Neural Nets**arXiv ID:** 2207.03577 **Authors:** Roland Olsson, Chau Tran, Lars Magnusson **Published:** 2022-06-29T06:35:06Z **Abstract:** We present a new class of neurons, ARNs, which give a cross entropy on test data that is up to three times lower than the one achieved by carefully optimized LSTM neurons. The explanations for the huge improvements that often are achieved are elaborate skip connections through time, up to four internal memory states per neuron and a number of novel activation functi...Votes: 0GitHub stars: 3
- Biophysics Informed Deep Operator LearningElectrophysiological source reconstruction with biophysics.Votes: 0GitHub stars: 3
- Carleman Linearization Ode SolverCarleman linearization methodology for converting nonlinear ODEs into infinite-dimensional linear systems via tensor powers. C2 (2nd order truncation) recovers both transient and steady-state solutions. Use when: (1) solving nonlinear differential equations, (2) quantum algorithms for ODEs (HHL-based), (3) fluid dynamics steady-state approximation, (4) converting nonlinear systems to linear form for quantum computation, (5) numerical analysis of dynamical systems. Keywords: carleman lineariza...Votes: 0GitHub stars: 3
- Classical Disjunction Effect ModelClassical probability model that reproduces the disjunction effect via expectation-parameter partitioning, proving classical and quantum-like models have equivalent expressiveness for decision rates.Votes: 0GitHub stars: 3
- Code Modulated Motion Vep BciCode-Modulated Motion Visual Evoked Potential (c-MVEP) methodology for brain-computer interfacing. Uses pseudo-random motion sequences instead of flickering for visual stimulation. Covers EEG-based BCI paradigms comparing c-MVEP, c-VEP, SSMVEP, SSVEP. Based on Scheppink et al. (arXiv: 2605.15801). Use when designing motion-based BCI systems, developing flicker-free visual stimulation paradigms, or comparing VEP-based BCI approaches. Activation: c-MVEP, motion VEP, code-modulated VEP, brain-co...Votes: 0GitHub stars: 3
- Continuous Antbased Neural Topology Search**arXiv ID:** 2011.10831 **Authors:** AbdElRahman ElSaid, Joshua Karns, Zimeng Lyu, Alexander Ororbia, Travis Desell **Published:** 2020-11-21T17:49:44Z **Abstract:** This work introduces a novel, nature-inspired neural architecture search (NAS) algorithm based on ant colony optimization, Continuous Ant-based Neural Topology Search (CANTS), which utilizes synthetic ants that move over a continuous search space based on the density and distribution of pheromones, is strongly inspired by how an...Votes: 0GitHub stars: 3
- Continuous Spiking Graph Neural Networks**arXiv ID:** 2404.01897 **Authors:** Nan Yin, Mengzhu Wan, Li Shen, Hitesh Laxmichand Patel, Baopu Li, Bin Gu, Huan Xiong **Published:** 2024-04-02T12:36:40Z **Abstract:** Continuous graph neural networks (CGNNs) have garnered significant attention due to their ability to generalize existing discrete graph neural networks (GNNs) by introducing continuous dynamics. They typically draw inspiration from diffusion-based methods to introduce a novel propagation scheme, which is analyzed using ord...Votes: 0GitHub stars: 3
- Controlled Dynamics Attractor Transformer**arXiv ID:** 2606.15207 **Authors:** Cheng Zhang, Minnan Luo, Zesheng Yang, Ming Li, Yong-Jin Liu, Qinghua Zheng **Published:** 2026-06-13T09:04:22Z **Abstract:** Transformer architectures have dramatically advanced representation learning and inference in deep models through self-attention mechanisms. In parallel,associative memory (AM) frameworks map representations onto energy landscapes, offering interpretable retrieval mechanisms. However, their continuous-time inference dynamics lack t...Votes: 0GitHub stars: 3
- Cross Modal Convergence ModulationModulating Cross-Modal Convergence with Single-Stimulus, Intra-Modal Dispersion - neural network methodology for modulating representational convergence across architectures and modalities. Reveals how single-stimulus dispersion within modalities predicts cross-modal alignment. Based on arXiv:2604.21836.Votes: 0GitHub stars: 3
- Cross Modal ConvergenceCross-modal representational convergence methodology using Generalized Procrustes Algorithm to measure intra-modal dispersion at single-stimulus level. Low intra-modal dispersion predicts up to 2× higher cross-modal alignment. Activation: representational similarity, RSA, Procrustes, cross-modal, model-brain alignment, vision-language, DINOv2.Votes: 0GitHub stars: 3
- Cross Modal Dispersion ConvergenceCross-modal convergence analysis methodology using Generalized Procrustes Algorithm to measure intra-modal representational convergence at single-stimulus level. Reveals how low intra-modal dispersion (high agreement among vision models) elicits significantly higher cross-modal alignment between vision and language models. Activation: cross-modal convergence, representational alignment, Procrustes analysis, vision-language alignment, neural representation, single-stimulus analysisVotes: 0GitHub stars: 3
- Debate On Graph Reliable And Adaptive Reasoning OfDerived from arXiv:2607.17266 - Debate-on-Graph: Reliable and Adaptive Reasoning of Large Language Model on Uncertain Knowledge GraphVotes: 0GitHub stars: 3
- Degree Tensor Train VarietiesIntegral geometry methodology for computing degrees of tensor train varieties.Votes: 0GitHub stars: 3
- Devotg Temporal Graph ConnectomicsDevoTG: Temporal Graph Neural Networks for modeling C. elegans developmental connectomics, capturing dynamic wiring through continuous-time and discrete-time dynamic graphs.Votes: 0GitHub stars: 3