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Showing 11,569–11,592 of 21,402 skills
- Geometric Brain Dynamics Mapping V3Geometric Basis Functions (GBF) framework for noninvasive whole human brain dynamics mapping. Uses participant-specific eigenmodes from cortical surface to resolve inverse problem in EEG/MEG source imaging. Activation: brain dynamics, geometric basis functions, source imaging, EEG/MEG, cortical geometry.Votes: 0GitHub stars: 3
- Winning The Lottery By Preserving Network Training Dynamics With Concrete Ticket Search**arXiv ID:** 2512.07142 **Authors:** Tanay Arora, Christof Teuscher **Published:** 2025-12-08T03:48:51Z **Abstract:** The Lottery Ticket Hypothesis asserts the existence of highly sparse, trainable subnetworks ('winning tickets') within dense, randomly initialized neural networks. However, state-of-the-art methods of drawing these tickets, like Lottery Ticket Rewinding (LTR), are computationally prohibitive, while more efficient saliency-based Pruning-at-Initialization (PaI) techniques suffe...Votes: 0GitHub stars: 3
- What Causes Polysemanticity An Alternative Origin Story Of Mixed Selectivity From Incidental Causes**arXiv ID:** 2312.03096 **Authors:** Victor Lecomte, Kushal Thaman, Rylan Schaeffer, Naomi Bashkansky, Trevor Chow, Sanmi Koyejo **Published:** 2023-12-05T19:29:54Z **Abstract:** Polysemantic neurons -- neurons that activate for a set of unrelated features -- have been seen as a significant obstacle towards interpretability of task-optimized deep networks, with implications for AI safety. The classic origin story of polysemanticity is that the data contains more ``features" than neurons, suc...Votes: 0GitHub stars: 3
- Weighted Regularization Deepc NonlinearData-driven predictive control (DeePC) framework for nonlinear systems that localizes the predictor by weighting data columns according to proximity to the current operating point, retaining the full data matrix and its rank for guaranteed feasibility. Activation: DeePC, data-enabled predictive control, Willems fundamental lemma, nonlinear MPC, weighted regularization, operating-point localization, data-driven control.Votes: 0GitHub stars: 3
- Virtual Distillation BosonicVirtual distillation framework extended to bosonic quantum systems using passive linear-optical interferometers for error-mitigated measurements in continuous-variable quantum computing.Votes: 0GitHub stars: 3
- Untrained Cnns Match Backpropagation V Systematicbackpropagation convolutional cortex cortical fmri methodology from arXiv:2604.16875. A central question in computational neuroscience is whether the learning rule used to train a neural network determines how well its internal represen... Activation: backpropagation, convolutional, cortex, cortical, fmri, learning rule, neural, plasticity, representational, rsaVotes: 0GitHub stars: 3
- Universal Complementarity IdentityUniversal complementarity identity for quantum interferometry — exact trade-off relation between path distinguishability and interference visibility for polarized double-slit experiments, with extensions to quantum information protocols. Activation: complementarity identity, wave-particle duality, quantum interferometry, path-visibility trade-off.Votes: 0GitHub stars: 3
- Trustssl Additiveresidual Selective Invariance For Robust Aerial Selfsupervised Learning**arXiv ID:** 2604.21349 **Authors:** Wadii Boulila, Adel Ammar, Bilel Benjdira, Maha Driss **Published:** 2026-04-23T07:07:59Z **Abstract:** Self-supervised learning (SSL) is a standard approach for representation learning in aerial imagery. Existing methods enforce invariance between augmented views, which works well when augmentations preserve semantic content. However, aerial images are frequently degraded by haze, motion blur, rain, and occlusion that remove critical evidence. Enforcing ...Votes: 0GitHub stars: 3
- Trial Trajectory Relative Hindsight DistillationTRIAL for trajectory-relative hindsight distillation in RL.Votes: 0GitHub stars: 3
- Transfer Dynamics In Emergent Evolutionary Curricula**arXiv ID:** 2203.10941 **Authors:** Aaron Dharna, Amy K Hoover, Julian Togelius, L. B. Soros **Published:** 2022-03-03T21:10:22Z **Abstract:** PINSKY is a system for open-ended learning through neuroevolution in game-based domains. It builds on the Paired Open-Ended Trailblazer (POET) system, which originally explored learning and environment generation for bipedal walkers, and adapts it to games in the General Video Game AI (GVGAI) system. Previous work showed that by co-evolving levels an...Votes: 0GitHub stars: 3
- Time Evidence Fusion Network Multisource View In Longterm Time Series Forecasting**arXiv ID:** 2405.06419 **Authors:** Tianxiang Zhan, Yuanpeng He, Yong Deng, Zhen Li, Wenjie Du, Qingsong Wen **Published:** 2024-05-10T12:10:22Z **Abstract:** In practical scenarios, time series forecasting necessitates not only accuracy but also efficiency. Consequently, the exploration of model architectures remains a perennially trending topic in research. To address these challenges, we propose a novel backbone architecture named Time Evidence Fusion Network (TEFN) from the perspective ...Votes: 0GitHub stars: 3
- Teacherstudent Curriculum LearningSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Stochastic Physical Neural NetworksStochastic Physical Neural Networks (PNNs) methodology using single-electron and single-photon stochastic neurons. Training via empirical backward pass with few trials achieves >97% MNIST accuracy. Use when: physical neural networks, stochastic neurons, single-electron tunneling, quantum dot neurons, single-photon neurons, PNN training strategies, MNIST classification, noise-resilient deep learning, arXiv:2604.10861, stochastic physical computing, quantum neurons.Votes: 0GitHub stars: 3
- Speculative Sparse Attention StsTraining-free sparse attention using draft model attention scores to construct dynamic token-and-head-wise sparsity masks for LLM inference. Achieves 2.67x speedup at ~90% sparsity with negligible accuracy loss.Votes: 0GitHub stars: 3
- Some Considerations On Learning To Explore Via MetSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Smooth Tchebycheff Scalarization For Multiobjective Optimization**arXiv ID:** 2402.19078 **Authors:** Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang **Published:** 2024-02-29T12:03:05Z **Abstract:** Multi-objective optimization problems can be found in many real-world applications, where the objectives often conflict each other and cannot be optimized by a single solution. In the past few decades, numerous methods have been proposed to find Pareto solutions that represent optimal trade-offs among the objectives for a given probl...Votes: 0GitHub stars: 3
- Simulation Inference Neural Network StructureSimulation-based inference of neural network structure from simple spike train statistics. Uses empirical spike frequency and interspike interval distributions instead of cross-correlation. Overcomes under-sampling limitation. Activation: network inference, spike train, connectivity estimation, simulation-based inference.Votes: 0GitHub stars: 3
- Self Initiated Attention Shifts EegSubject-specific analysis of self-initiated attention shifts from EEG with controlled internal and external attention conditions. Machine learning + SHAP feature attribution reveals that higher-frequency bands and frontal regions carry subject-specific discriminative information for distinguishing self-initiated vs externally-cued attention shifts (arXiv:2605.18251). Use for EEG attention decoding, self-initiated attention research, voluntary attention neural correlates, SHAP-based EEG interp...Votes: 0GitHub stars: 3
- Sampling On Random Subspaces Under Limited Data InSampling on Random Subspaces under Limited Data in the Context of Exploratory Landscape Analysis. Classical space-filling designs often fail to provide reliable statistical results for Exploratory Landscape Analysis (ELA) when only limited evaluation budgets are available, as commonly occurs in hi... Activation: benchmark, optimization, lora, robustness, embeddingVotes: 0GitHub stars: 3
- Rlcsd Contrastive On Policy DistillationContrastive on-policy self-distillation methodology for reasoning models that mitigates privilege-induced style driftVotes: 0GitHub stars: 3
- Reptile A Scalable Meta Learning AlgorithmSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Representation Use Usability FrameworkUnified framework for representation use and usability across philosophy, neuroscience, cognitive science, and computer science. Analyzes when and how representations are used effectively in different systems. Trigger words: representation usability, representation use, philosophical representation, cognitive representation, AI representation theory.Votes: 0GitHub stars: 3
- Representation SteeringLLM representation steering and activation patching methodology for mechanistic interpretability. Use when analyzing how steering vectors affect LLM internals, conducting activation patching experiments, or investigating causal mechanisms in neural networks. Keywords: representation steering, activation patching, mechanistic interpretability, steering vectors, OV circuit, QK circuit, refusal steering.Votes: 0GitHub stars: 3
- Reopd Multi Turn On Policy DistillationReOPD (Replayed-Prefix On-Policy Distillation) methodology for scalable multi-turn agent distillation without environment interaction during training. Addresses the 'prefix trap' in multi-turn OPD via reliability-aware prefix sampling.Votes: 0GitHub stars: 3