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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Paving The Way For Agents In BiologyPaving the way for agents in biologyVotes: 0GitHub stars: 3
- Persistent Homology Brain Network ControlPersistent homology methodology for brain network control that broadens the controllable subspace in human structural connectomes. Uses topological cycles to identify driver nodes beyond traditional degree-based selection, revealing dissociation between control cost and control geometry. Use when analyzing brain network controllability, structural connectomes, or topological neuroscience applications.Votes: 0GitHub stars: 3
- Perspective Latents Causal Emergence Active InferenceFramework for measuring causal emergence (ΦID) in active inference agents with perspective latents architecture, analyzing how architectural separation between fast perception and slow global latents affects information-theoretic signatures of integration. Use when studying causal emergence, active inference, or hierarchical agent architectures.Votes: 0GitHub stars: 3
- Phinn Eeg Topological Dream AnalysisTopological time-series (TDA) framework for EEG analysis — sliding-window Takens delay embeddings + Vietoris-Rips filtrations to extract Dynamic Betti Curves, then topology-conditioned flow matching / rectified flow for neural signal synthesis and rare-event (dream-state) detection. Use when analyzing multichannel EEG/EMG time series where spectral-energy features (PSD, catch22) plateau, when building EEG foundation/synthesis models, or when studying dream-state / consciousness / sleep neural...Votes: 0GitHub stars: 3
- A Graph Native Bitemporal Memory Store For ConversA Graph-Native Bitemporal Memory Store for Conversational AI AgentsVotes: 0GitHub stars: 3
- A Lite Fireworks Algorithm With Fractal Dimension Constraint For Feature Selection**arXiv ID:** 2303.05516 **Authors:** Min Zeng, Haimiao Mo, Zhiming Liang, Hua Wang **Published:** 2023-03-09T01:52:54Z **Abstract:** As the use of robotics becomes more widespread, the huge amount of vision data leads to a dramatic increase in data dimensionality. Although deep learning methods can effectively process these high-dimensional vision data. Due to the limitation of computational resources, some special scenarios still rely on traditional machine learning methods. However, these ...Votes: 0GitHub stars: 3
- A Logical Reconception Of Neural Networks Hamiltonian Bitwise Partwhole Architecture**arXiv ID:** 2602.04911 **Authors:** E Bowen, R Granger, A Rodriguez **Published:** 2026-02-04T01:16:37Z **Abstract:** We introduce a simple initial working system in which relations (such as part-whole) are directly represented via an architecture with operating and learning rules fundamentally distinct from standard artificial neural network methods. Arbitrary data are straightforwardly encoded as graphs whose edges correspond to codes from a small fixed primitive set of elemental pairwise...Votes: 0GitHub stars: 3
- A Monadbased Clause Architecture For Artificial Age Score Aas In Large Language Models**arXiv ID:** 2512.11835 **Authors:** Seyma Yaman Kayadibi **Published:** 2025-12-03T12:48:40Z **Abstract:** Large language models (LLMs) are often deployed as powerful yet opaque systems, leaving open how their internal memory and "self-like" behavior should be governed in a principled and auditable way. The Artificial Age Score (AAS) was previously introduced and mathematically justified through three theorems that characterise it as a metric of artificial memory aging. Building on this fou...Votes: 0GitHub stars: 3
- Accurate Deep Learning Subgrid Scale Models For Large Eddy Simulations**arXiv ID:** 2307.10060 **Authors:** Rikhi Bose, Arunabha M. Roy **Published:** 2023-07-19T15:30:06Z **Abstract:** We present two families of sub-grid scale (SGS) turbulence models developed for large-eddy simulation (LES) purposes. Their development required the formulation of physics-informed robust and efficient Deep Learning (DL) algorithms which, unlike state-of-the-art analytical modeling techniques can produce high-order complex non-linear relations between inputs and outputs. Explici...Votes: 0GitHub stars: 3
- Advanced Displacement Magnitude Prediction In Multimaterial Architected Lattice Structure Beams Using Physics Informed Neural Network Architecture**arXiv ID:** 2501.03254 **Authors:** Akshansh Mishra **Published:** 2024-12-31T00:15:58Z **Abstract:** This paper proposes an innovative method for predicting deformation in architected lattice structures that combines Physics-Informed Neural Networks (PINNs) with finite element analysis. A thorough study was carried out on FCC-based lattice beams utilizing five different materials (Structural Steel, AA6061, AA7075, Ti6Al4V, and Inconel 718) under varied edge loads (1000-10000 N). The PINN m...Votes: 0GitHub stars: 3
- Aha Wam Async World Action ModelingAHA-WAM - Asynchronous Horizon-Adaptive World-Action Model for robot manipulation. Dual DiT architecture with low-frequency world planner and high-frequency action expert. Features observation-guided video-context routing (OVCR), horizon-adaptive offset training, and real-time closed-loop control at 24.17Hz. Use for: async temporal modeling, world-action coupling, real-time control, long-horizon planning.Votes: 0GitHub stars: 3
- Anncrips Artificial Neural Networks For Cancer Research In Prediction Survival**arXiv ID:** 2309.15803 **Authors:** Amit Mathapati **Published:** 2023-09-26T08:11:35Z **Abstract:** Prostate cancer is a prevalent malignancy among men aged 50 and older. Current diagnostic methods primarily rely on blood tests, PSA:Prostate-Specific Antigen levels, and Digital Rectal Examinations (DRE). However, these methods suffer from a significant rate of false positive results. This study focuses on the development and validation of an intelligent mathematical model utilizing Artific...Votes: 0GitHub stars: 3
- Approximate Spectral Clustering With Eigenvector Selection And Selftuned K**arXiv ID:** 2302.11297 **Authors:** Mashaan Alshammari, Masahiro Takatsuka **Published:** 2023-02-22T11:32:24Z **Abstract:** The recently emerged spectral clustering surpasses conventional clustering methods by detecting clusters of any shape without the convexity assumption. Unfortunately, with a computational complexity of $O(n^3)$, it was infeasible for multiple real applications, where $n$ could be large. This stimulates researchers to propose the approximate spectral clustering (ASC). ...Votes: 0GitHub stars: 3
- Approximation Theory For Neural Networks Old And New**arXiv ID:** 2605.21451 **Authors:** Soumendu Sundar Mukherjee, Himasish Talukdar **Published:** 2026-05-20T17:42:34Z **Abstract:** Universal approximation theorems provide a mathematical explanation for the expressive power of neural networks. They assert that, under mild conditions on the activation function, feedforward neural networks are dense in broad function classes, such as continuous functions on compact subsets of $\mathbb{R}^d$, $L^p$ spaces, or Sobolev spaces. Over the past four...Votes: 0GitHub stars: 3
- Aptx Better Activation Function Than Mish Swish And Relus Variants Used In Deep Learning**arXiv ID:** 2209.06119 **Authors:** Ravin Kumar **Published:** 2022-09-10T14:26:04Z **Abstract:** Activation Functions introduce non-linearity in the deep neural networks. This nonlinearity helps the neural networks learn faster and efficiently from the dataset. In deep learning, many activation functions are developed and used based on the type of problem statement. ReLU's variants, SWISH, and MISH are goto activation functions. MISH function is considered having similar or even better per...Votes: 0GitHub stars: 3
- Arxiv 2605 01107 Diffusion Operator Geometry Of Feedforward RepreseDiffusion Operator Geometry of Feedforward Representations (arXiv: 2605.01107)Votes: 0GitHub stars: 3
- Arxiv 2608 05455 Stochasticity Is Not The Hard Part Reduction And CStochasticity Is Not the Hard Part: Reduction and Complexity in Instructional Sequencing over Prerequisite DAGs (arXiv: 2608.05455)Votes: 0GitHub stars: 3
- Arxiv 2608 05724v1 Sparse Mutual Information Graph Averaging For Impr**arXiv ID:** 2608.05724v1 **Authors:** Sriram Loganathan, Gokul Anand, Aung Bo Bo, Yourui Shao, William B. Andreopoulos **URL:** http://arxiv.org/abs/2608.05724v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 05833 Visr Kgc Visual Subgraph Reasoning With Vision LanViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion (arXiv: 2608.05833)Votes: 0GitHub stars: 3
- Arxiv 2608 05833v1 Visr Kgc Visual Subgraph Reasoning With Vision Lan**arXiv ID:** 2608.05833v1 **Authors:** Jiafan Li, Mengxue Yang, Jiaqi Zhu, Liang Chang, Ying Li, Hongan Wang **URL:** http://arxiv.org/abs/2608.05833v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 05910v1 Coursegraph Finding Overlaps And Differences In Co**arXiv ID:** 2608.05910v1 **Authors:** Arthur Nijdam, Paul Stankovski Wagner, Sara Ramezanian **URL:** http://arxiv.org/abs/2608.05910v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 05928v1 Biom Jepa Joint Embedding Prediction Of Graph Conn**arXiv ID:** 2608.05928v1 **Authors:** Yuhao Wang, Zelin Zang, Yuxuan Liu, Zhen Lei, Stan Z. Li **URL:** http://arxiv.org/abs/2608.05928v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 05982v1 Thbkg A Temporal Biomedical Knowledge Graph For De**arXiv ID:** 2608.05982v1 **Authors:** Pui Chung Siu, Claudia Cabrera, Mani Mudaliar, Arkaitz Zubiaga **URL:** http://arxiv.org/abs/2608.05982v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 06031v1 Dynamic Graph Prompting Via Topology Routed Mixed**arXiv ID:** 2608.06031v1 **Authors:** Quanxin Wang, Xuanting Xie, Bingheng Li, Xingtong Yu, Shuo Wang, Ruiyi Fang, Zhao Kang **URL:** http://arxiv.org/abs/2608.06031v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 06107v1 Kastor An Efficient Fine Tuning Strategy For GenerKastor: An efficient fine-tuning strategy for generative emulation of PDE simulations (arXiv: 2608.06107v1)Votes: 0GitHub stars: 3
- Arxiv 2608 12982v1 Learning The Mathematical Property For Designing L**arXiv ID:** 2608.12982v1 **Authors:** Rekha, Santosh Singh, S. K. Neogy **URL:** http://arxiv.org/abs/2608.12982v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13212v1 Tangco Learning Topology Aware Capacity Allocation**arXiv ID:** 2608.13212v1 **Authors:** Orkun Irsoy, Leman Akoglu, Osman Yagan **URL:** http://arxiv.org/abs/2608.13212v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13305v1 Physics Informed Distribution Of Relaxation Times**arXiv ID:** 2608.13305v1 **Authors:** Žan Gorenc, Žiga Gradišar, Felix Mütter, Vanja Subotić, Pavle Boškoski **URL:** http://arxiv.org/abs/2608.13305v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13520v1 The Data Geometry Of Masking Diffusion Certified O**arXiv ID:** 2608.13520v1 **Authors:** Martin J. Wainwright **URL:** http://arxiv.org/abs/2608.13520v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18495v1 Physics Unrolled Neural Operator For Wireless Fiel**arXiv ID:** 2608.18495v1 **Authors:** Rafid Umayer Murshed, Saif Ur Rahman, Mingyue Tang, Elahe Soltanaghai **URL:** http://arxiv.org/abs/2608.18495v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18500v1 Tianmu Tc Physics Constraints Generative Artificia**arXiv ID:** 2608.18500v1 **Authors:** Shiqi Zhang, Pan Mu, Cheng Huang, Hanting Yan, Yuchao Zhu, Jinglin Zhang, Shengyong Chen, Shoujuan Shu, Cong Bai **URL:** http://arxiv.org/abs/2608.18500v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18522v1 Gcno Gramian Chebyshev Neural Operator For Physics**arXiv ID:** 2608.18522v1 **Authors:** Rafid Umayer Murshed, Shahab Hamidi-Rad, Elahe Soltanaghai, Akshay Malhotra **URL:** http://arxiv.org/abs/2608.18522v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18777v1 Graphk Variable Size Graph Generation With Efficie**arXiv ID:** 2608.18777v1 **Authors:** Resul Tugay, Eren Oluğ, Elif Ak, Sule Gunduz Oguducu **URL:** http://arxiv.org/abs/2608.18777v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18887v1 Graph Based Approaches To Learning Epileptogenic Z**arXiv ID:** 2608.18887v1 **Authors:** Daniel Wendelken, Brian Ervin, Ravindra Arya, Ali A. Minai **URL:** http://arxiv.org/abs/2608.18887v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18996v1 Grabvg Graph Attentive Binding For Visual Groundin**arXiv ID:** 2608.18996v1 **Authors:** Chaowei Wang, Yan Di, Jingjun Sun, Baozhe Liu, Jiaxu Tian, Yuheng Li, Guangqian Guo, Shan Gao **URL:** http://arxiv.org/abs/2608.18996v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 19965 Flow Matching Meets 3d Curvilinear Structure SegmeFlow Matching Meets 3D Curvilinear Structure Segmentation in Medical Imaging (arXiv: 2608.19965)Votes: 0GitHub stars: 3
- Arxiv 2608 20009 Exphy A Benchmark For Explicit Physical Property LExPhy: A Benchmark for Explicit Physical Property Learning in Multi-Object Trajectory Forecasting (arXiv: 2608.20009)Votes: 0GitHub stars: 3
- Arxiv 2608 22809v1 Sage Stability Aware Graph Based Ensemble Feature**arXiv ID:** 2608.22809v1 **Authors:** Md. Rokon Islam Emon, Syed Shariar Alam Shuvo, Shahriar Siddique Ayon, Abdullah Al Mamun, Ahnaf Atef Choudhury **URL:** http://arxiv.org/abs/2608.22809v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 22980v1 Hypergraph Embedding Indexing For Efficient Dense**arXiv ID:** 2608.22980v1 **Authors:** Kishore Konda **URL:** http://arxiv.org/abs/2608.22980v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23047v1 Beyond Verdicts A Graph Based Analysis Of Human An**arXiv ID:** 2608.23047v1 **Authors:** Abdul Ghafoor, Muhammad Arslan Manzoor, Yufang Hou **URL:** http://arxiv.org/abs/2608.23047v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23323v1 Mycelial Search A Graph Structured Metaheuristic F**arXiv ID:** 2608.23323v1 **Authors:** Mohammad Mahdi Dehshibi **URL:** http://arxiv.org/abs/2608.23323v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23375v1 Adversarial Entropy Inflation Against Gumbel Based**arXiv ID:** 2608.23375v1 **Authors:** Nikita Kezins **URL:** http://arxiv.org/abs/2608.23375v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25390v1 Refusal Geometry Reflects Refusal Training Diverse**arXiv ID:** 2608.25390v1 **Authors:** Andrey Labunets **URL:** http://arxiv.org/abs/2608.25390v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25564v1 Physics Informed Foresight Pruning For Sparse Pinn**arXiv ID:** 2608.25564v1 **Authors:** Ahmad Ishaque Karimi, Uvini Balasuriya Mudiyanselage, Kookjin Lee **URL:** http://arxiv.org/abs/2608.25564v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25741v1 Why Does Graph Learning Fail To Fully Benefit From**arXiv ID:** 2608.25741v1 **Authors:** Fumiaki Kimino, Ryoma Sato **URL:** http://arxiv.org/abs/2608.25741v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25744v1 A Constitutive Markov Physics Informed Neural Oper**arXiv ID:** 2608.25744v1 **Authors:** Wenpu Du, Peng Zhou, Yunlong Xia, Sinuo Xin, Congcong Zhang, Boyang Zhang, Yi Zhang, Wenzheng Xu **URL:** http://arxiv.org/abs/2608.25744v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25807v1 Geometry Constrained Kolmogorov Arnold Networks Le**arXiv ID:** 2608.25807v1 **Authors:** K S Sesh Kumar **URL:** http://arxiv.org/abs/2608.25807v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26549v1 Physics Informed Stochastic Configuration Machine**arXiv ID:** 2608.26549v1 **Authors:** Yuehao Song, Zhong Chen, Lihui Cen, Liang Wu, Kai Zhang **URL:** http://arxiv.org/abs/2608.26549v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26655v1 When Privacy Hurts Mergeability Geometry Aware Mod**arXiv ID:** 2608.26655v1 **Authors:** Jin Liu, Junkang Liu, Ning Xi, Yinbin Miao, Dawei Wei, Ke Cheng, Jianfeng Ma **URL:** http://arxiv.org/abs/2608.26655v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26656v1 Cogeo Gs Concept Driven And Geometry Aware Multi O**arXiv ID:** 2608.26656v1 **Authors:** Yuanxiang Ni, Xianliang Huang, Chenhang Ma, Chen Xiao, Yuewen Ma, Ruxin Wang, Hao Zhang **URL:** http://arxiv.org/abs/2608.26656v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3