All categories
Research
Research, evidence gathering, literature, reports, investigation, and synthesis
- 21,402
- 892
Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.
Open in full browserBrowse research skills
Showing 10,273–10,296 of 21,402 skills
- Glow Better Reversible Generative ModelsSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Generative ModelsSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Generative Modeling With Sparse TransformersSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Domain Randomization And Generative Models For RobSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Diffusion Learning Viable Parameter ManifoldsDiffusion models for learning viable parameter manifolds and compensation geometry in biological dynamical systems. Use when studying parameter degeneracy, model fitting, neural dynamics, or systems biology.Votes: 0GitHub stars: 3
- Dexverse A Modular Benchmark For Multi Task MultiDexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation. Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and... Activation: benchmark, diffusion, control, tool use, policyVotes: 0GitHub stars: 3
- Dalle Creating Images From TextSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Dalle 2 Pre Training MitigationsSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Computer Vision Neurology Brain Activity RejectionAutomated computer vision based ICA rejection labeling tool for EEG analysis that reduces processing time by 7200 fold and achieves 89.45% accuracyVotes: 0GitHub stars: 3
- Clip Connecting Text And ImagesSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Autopilot Vqa Benchmarking Vision Language Models For IncidentAUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding. Recent advances in Vision-Language Models, Large Language Models, and Multimodal Large Language Models have improved autonomous driving tasks such as scene understanding, decision making, trajectory p... Activation: benchmark, safety, reasoning, vision-language, multimodalVotes: 0GitHub stars: 3
- Arxiv 2609 04096v1 Adaptive Vision Language Grasping Via Composable F**arXiv ID:** 2609.04096v1 **Authors:** Sixu Yan, Shikang Wang, Binhua Huang, Xuanlai Tang, Guohua Fan, Fan Huang, Haoxuan Li, Yongkang Li, Yuhan Li, Bencheng Liao, Zeyu Zhang, Wenyu Liu, Hangxin Liu, Xinggang Wang **URL:** http://arxiv.org/abs/2609.04096v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 03382v1 Surgegen A Hybrid Generative Diffusion Framework F**arXiv ID:** 2609.03382v1 **Authors:** Shunan Zheng, John J. Hasenbein **URL:** http://arxiv.org/abs/2609.03382v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 20087 Towards Professional Tennis Styles For Humanoid RoTowards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking (arXiv: 2608.20087)Votes: 0GitHub stars: 3
- Arxiv 2608 20083 Sabet Qa Temporal Knowledge Graph Question AnsweriSABET-QA: Temporal Knowledge Graph Question Answering (arXiv: 2608.20083)Votes: 0GitHub stars: 3
- Arxiv 2608 19922 Auditing Recorded Predictive Lead Service Line ClaAuditing Recorded Predictive Lead Service-Line Classifications Against Physical Verification: A Statewide Study of New York (arXiv: 2608.19922)Votes: 0GitHub stars: 3
- Arxiv 2608 19906 Peta Parameter Efficient Test Time Adaptation ForPETA:Parameter-Efficient Test-Time Adaptation for Virtual Screening (arXiv: 2608.19906)Votes: 0GitHub stars: 3
- Arxiv 2608 13368v1 Sign Language Video Synthesis Via Loss Guided Mult**arXiv ID:** 2608.13368v1 **Authors:** Dingzhan Nong, Zhihao Ren, Ziqi Li, Tim Lo **URL:** http://arxiv.org/abs/2608.13368v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Aigb R1 Self Evolving Generative Auto Bidding Hierarchical Planner Executor OptimizationSkill derived from arXiv:2607.17281 - AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor OptimizationVotes: 0GitHub stars: 3
- A Survey On Evolutionary Computation For Computer Vision And Image Analysis Past Present And Future Trends**arXiv ID:** 2209.06399 **Authors:** Ying Bi, Bing Xue, Pablo Mesejo, Stefano Cagnoni, Mengjie Zhang **Published:** 2022-09-14T03:35:25Z **Abstract:** Computer vision (CV) is a big and important field in artificial intelligence covering a wide range of applications. Image analysis is a major task in CV aiming to extract, analyse and understand the visual content of images. However, image-related tasks are very challenging due to many factors, e.g., high variations across images, high dimensi...Votes: 0GitHub stars: 3
- A Connection Between Generative Adversarial NetworSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Qnd Measurements Fault Tolerant Biased NoiseQuantum non-demolition (QND) multi-qubit Pauli measurements as a practical primitive for fault-tolerant quantum computation against biased noise. Replaces bias-preserving CNOT gates with QND ZZ measurements, enabling 6× qubit overhead reduction. arXiv: 2605.24262Votes: 0GitHub stars: 3
- Ven Circuit Snn Social LearningVENCircuit methodology — Von Economo neurons (VENs) as acquisition scaffolds in recurrent spiking neural networks. Combines computational modeling with clinical predictions for bvFTD and autism. Use when: studying VENs, social learning in SNNs, gradient pathway analysis, clinical prediction from computational models, developmental scaffolding in neural networks.Votes: 0GitHub stars: 3
- Unsupervised Anomaly Detection In Stream Data With Online Evolving Spiking Neural Networks**arXiv ID:** 1912.08785 **Authors:** Piotr S. Maciąg, Marzena Kryszkiewicz, Robert Bembenik, Jesus L. Lobo, Javier Del Ser **Published:** 2019-12-18T18:36:01Z **Abstract:** Unsupervised anomaly discovery in stream data is a research topic with many practical applications. However, in many cases, it is not easy to collect enough training data with labeled anomalies for supervised learning of an anomaly detector in order to deploy it later for identification of real anomalies in streaming data...Votes: 0GitHub stars: 3