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- Neural Quantum State Vqmc CorrelatedNeural network quantum state (NQS) variational Monte Carlo for correlated superconducting nanostructures. Maps quantum dot clusters to particle-number-conserving representations for fermionic NQS-VMC treatment. Identifies trivial singlet, strongly correlated Heisenberg, and critical intermediate regimes. 1D singlet-doublet transitions, 2D robust triplet ground states. Use when studying correlated superconducting systems, quantum dot arrays, or fermionic neural quantum states.Votes: 0GitHub stars: 3
- Memoryvla Temporal Modeling Robotic ManipulationMemoryVLA++ - Temporal modeling framework for VLA models with memory and imagination mechanisms for robotic manipulation. Includes working memory, perceptual-cognitive memory bank, world model for future state imagination, and diffusion action expert. Use for: long-horizon tasks, memory-dependent manipulation, temporal consistency, world prediction, robotic control.Votes: 0GitHub stars: 3
- Free Energy Rl InvestmentFree Energy-Entropy Duality methodology for risk-sensitive reinforcement learning in continuous-time investment management. Reformulates benchmarked asset allocation as a linear-quadratic-Gaussian stochastic differential game under an equivalent probability measure.Votes: 0GitHub stars: 3
- Computation With Sequences In A Model Of The Brain**arXiv ID:** 2306.03812 **Authors:** Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala **Published:** 2023-06-06T15:58:09Z **Abstract:** Even as machine learning exceeds human-level performance on many applications, the generality, robustness, and rapidity of the brain's learning capabilities remain unmatched. How cognition arises from neural activity is a central open question in neuroscience, inextricable from the study of intelligence itself. A simple formal model of neural activ...Votes: 0GitHub stars: 3
- A Neurocomputational Account Of Flexible Goaldirected Cognition And Consciousness The Goalaligning Representation Internal Manipulation Theory Garim**arXiv ID:** 1912.13490 **Authors:** Giovanni Granato, Gianluca Baldassarre **Published:** 2019-12-31T18:45:33Z **Abstract:** Goal-directed manipulation of representations is a key element of human flexible behaviour, while consciousness is often related to several aspects of higher-order cognition and human flexibility. Currently these two phenomena are only partially integrated (e.g., see Neurorepresentationalism) and this (a) limits our understanding of neuro-computational processes that ...Votes: 0GitHub stars: 3
- A Frugal Spiking Neural Network For Unsupervised Classification Of Continuous Multivariate Temporal Data**arXiv ID:** 2408.12608 **Authors:** Sai Deepesh Pokala, Marie Bernert, Takuya Nanami, Takashi Kohno, Timothée Lévi, Blaise Yvert **Published:** 2024-08-08T08:15:51Z **Abstract:** As neural interfaces become more advanced, there has been an increase in the volume and complexity of neural data recordings. These interfaces capture rich information about neural dynamics that call for efficient, real-time processing algorithms to spontaneously extract and interpret patterns of neural dynamics. M...Votes: 0GitHub stars: 3
- Neuroscience Graph Operators Virtual SensingNeuroscience-inspired graph neural operators for edge-deployable virtual sensing on irregular geometries. Enables sparse-to-dense reconstruction and real-time full-field physics prediction with latency and energy constraints.Votes: 0GitHub stars: 3
- Neuronal Arithmetic OtsNeuronal arithmetic operators using Ovonic Threshold Switches (OTS) for biologically inspired analog computing. Implements additive integration and divisive gain modulation through synaptic conductance changes and shunting inhibition. Trigger words: Ovonic threshold switch, neuronal arithmetic, analog computing, biologically inspired computing, shunting inhibition, gain modulation, synaptic conductance, neuromorphic arithmetic, OTS neuron, additive integration, divisive normalization.Votes: 0GitHub stars: 3
- Neuromorphic Spacecraft Pose Event CameraEnd-to-end spacecraft 6-DoF pose estimation using event cameras and BrainChip Akida neuromorphic processor. MobileNet-style keypoint regression on event-frame representations with quantization-aware training (8/4-bit) converted to spiking neural networks. First demonstration of spacecraft pose estimation on Akida hardware. Activation: neuromorphic, event camera, spacecraft pose, Akida, spiking neural network, space robotics, event-based vision.Votes: 0GitHub stars: 3
- Neuro Vesicles NeuromodulationNeuro-Vesicles framework for dynamical neuromodulation in neural networks. Introduces mobile discrete vesicle population as event-based interaction layer alongside network tensors. Applies to: neuromodulation, dynamic network modulation, spiking networks, neuromorphic hardware. Activation: neuro vesicles, neuromodulation dynamical, mobile modulation, vesicle framework, programmable neuromodulation.Votes: 0GitHub stars: 3
- Multi Scale Information Geometry NeuralMulti-scale information geometry framework for analyzing neural population codes. Extends Fisher information metric across stimulus coarse-graining scales to reveal mutual information structure. Use when analyzing: (1) neural population coding geometry, (2) Fisher information limitations in neural data, (3) representational geometry from first principles, (4) mutual information estimation from neural responses, (5) diffusion model-based neural encoding analysis. Trigger: multi-scale Fisher, i...Votes: 0GitHub stars: 3
- Semiconductor Fab Scheduling With Selfsupervised And Reinforcement Learning**arXiv ID:** 2302.07162 **Authors:** Pierre Tassel, Benjamin Kovács, Martin Gebser, Konstantin Schekotihin, Patrick Stöckermann, Georg Seidel **Published:** 2023-02-14T16:15:50Z **Abstract:** Semiconductor manufacturing is a notoriously complex and costly multi-step process involving a long sequence of operations on expensive and quantity-limited equipment. Recent chip shortages and their impacts have highlighted the importance of semiconductors in the global supply chains and how reliant on...Votes: 0GitHub stars: 3
- Rl Ion ShuttlingReinforcement learning for ion shuttling optimization on trapped-ion quantum computersVotes: 0GitHub stars: 3
- Implicit Twotower Policies**arXiv ID:** 2208.01191 **Authors:** Yunfan Zhao, Qingkai Pan, Krzysztof Choromanski, Deepali Jain, Vikas Sindhwani **Published:** 2022-08-02T01:23:50Z **Abstract:** We present a new class of structured reinforcement learning policy-architectures, Implicit Two-Tower (ITT) policies, where the actions are chosen based on the attention scores of their learnable latent representations with those of the input states. By explicitly disentangling action from state processing in the policy stack, we...Votes: 0GitHub stars: 3
- Evolutionary Deep Reinforcement Learning For Dynamic Slice Management In Oran**arXiv ID:** 2208.14394 **Authors:** Fatemeh Lotfi, Omid Semiari, Fatemeh Afghah **Published:** 2022-08-30T17:00:53Z **Abstract:** The next-generation wireless networks are required to satisfy a variety of services and criteria concurrently. To address upcoming strict criteria, a new open radio access network (O-RAN) with distinguishing features such as flexible design, disaggregated virtual and programmable components, and intelligent closed-loop control was developed. O-RAN slicing is bein...Votes: 0GitHub stars: 3
- Deep Reinforcement Learning Framework For Diversified Portfolio Management Across Global Equity Markets**arXiv ID:** 2605.17307 **Authors:** Kamil Kashif, Robert Ślepaczuk **Published:** 2026-05-17T07:50:37Z **Abstract:** This study develops and evaluates a deep reinforcement learning framework for dynamic portfolio allocation across global equity markets. The Soft Actor-Critic algorithm is used to learn continuous portfolio weights within a Markov Decision Process, incorporating transaction costs, turnover penalties, and diversification constraints into the reward function. Five model configu...Votes: 0GitHub stars: 3
- Arxiv 2608 20038 An Inclusive And Lightweight Approach To FederatedAn Inclusive and Lightweight Approach to Federated Continual Learning for Cultural Heritage (arXiv: 2608.20038)Votes: 0GitHub stars: 3
- Mpc Stability SuboptimalityModel Predictive Control (MPC) stability and suboptimality analysis under plant-model mismatch. Covers discounted and undiscounted infinite-horizon optimal control, stability guarantees with model uncertainty, and suboptimality bounds. Use when analyzing MPC robustness, handling model-plant mismatch in control systems, or implementing robust MPC controllers.Votes: 0GitHub stars: 3
- Modular Quantum Shor CompilationDistributed compilation of Shor's algorithm on modular atomic quantum processors. Methodology for large-scale integer factorization across multiple quantum modules with optimized inter-module communication and intra-module clock rates. Use when: compiling Shor's algorithm for distributed quantum hardware, designing modular quantum architectures, optimizing quantum communication between modules, analyzing resource requirements for large-scale factoring, or planning fault-tolerant quantum crypt...Votes: 0GitHub stars: 3
- Mmpo Metacognitive Memory PolicyMeta-Cognitive Memory Policy Optimization (MMPO) for long-horizon LLM agents using Belief Entropy as self-supervised proxy.Votes: 0GitHub stars: 3
- Ml Clifford Noise ReductionML-guided Clifford noise reduction for Hamiltonian simulations using mid-circuit measurements. Use when optimizing quantum circuit noise, designing stabilizer verification protocols, reducing logical error rates in encoded quantum operations, or applying ML to select optimal quantum verification operators. Covers CliNR framework, symplectic transvection Trotter synthesis, and ML-guided stabilizer selection. Activation: quantum noise reduction, Clifford noise, CliNR, stabilizer verification, m...Votes: 0GitHub stars: 3
- Meta Representational Predictive CodingMeta-Representational Predictive Coding (MPC) — encoder-only neuroscience-informed self-supervised learning within the free energy principle, using cross-stream latent prediction and active inference saccade planning instead of backpropagation (arXiv: 2503.21796v2)Votes: 0GitHub stars: 3
- Memorywam Efficient World Action ModelingMemoryWAM introduces persistent memory mechanisms for efficient world-action modeling with world model integration and hippocampal-inspired memory consolidation.Votes: 0GitHub stars: 3
- Neuroclaw Multimodal NeuroimagingNeuroClaw - Domain-specialized multi-agent research assistant for executable and reproducible neuroimaging research. Supports heterogeneous modalities (sMRI, fMRI, dMRI, EEG), BIDS metadata integration, environment management, and three-tier skill/agent hierarchy. Use for automated neuroimaging pipelines, reproducible research workflows, and multi-modal brain data analysis. Keywords: neuroimaging, BIDS, multi-agent, reproducible research, fMRI, sMRI, dMRI, EEG.Votes: 0GitHub stars: 3