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Testing & QA
Unit tests, integration tests, E2E, QA, validation, and test automation
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- Quantum Optimization Landscape AnalysisQuantum optimization landscape analysis methodology for NISQ-era variational algorithms. Covers VQE/QAOA performance analysis, expressibility-noise barren plateaus, feedback-guided methods (FALQON), and physics-informed circuit co-design for strongly correlated many-body systems. Activation: quantum optimization, VQE, QAOA, barren plateau, FALQON, feedback quantum algorithm, strongly correlated systems, many-body phase transitions, variational quantum algorithm, quantum criticality, expressib...Votes: 0GitHub stars: 3
- Quantum Ml RobustnessAnalyze and test Quantum Machine Learning (QML) model accuracy and robustness. Covers quantum neural network (QNN) robustness evaluation, mutation testing for quantum circuits, variational quantum circuit analysis, and scalability assessment for near-term quantum hardware. Use when evaluating QML model reliability, designing fault injection tests for quantum circuits, assessing QNN generalization, or preparing quantum algorithms for NISQ-era hardware deployment. Triggers: quantum ML robustnes...Votes: 0GitHub stars: 3
- Quantum Mirror TomographyQuantum mirror-based continuous-variable state tomography methodology. Transfers complete photonic state information onto a control atomic system for full characterization through kernel functions, direct wavefunction reconstruction, and pointwise Wigner function measurements. Overcomes exponential sample complexity of conventional CV tomography.Votes: 0GitHub stars: 3
- Quantum Histopathology Cancer DetectionQuantum algorithms for histopathologic cancer detection on real hardware (NISQ). Covers DG-CSWAP and DG-DST circuits, NISQ mitigation pipeline, and practical QPU validation strategies.Votes: 0GitHub stars: 3
- Quantum Cayley Llm AdaptersQuantum-enhanced LLM methodology using Cayley-parameterized unitary adapters to overcome classical memory scaling limits. Enables quantum circuit blocks in frozen transformer architectures for LLM fine-tuning on real quantum hardware.Votes: 0GitHub stars: 3
- Qlif Cast Weather ForecastingQLIF-CAST: Quantum Leaky-Integrate-and-Fire methodology for time-series regression (weather forecasting). Hybrid quantum-classical recurrent architecture using single-qubit superpositions for neuron states. Demonstrates 15.4% MSE reduction over classical LIF and 94% faster convergence vs QLSTM/QNN.Votes: 0GitHub stars: 3
- Qaoa Xy Mixers PortfolioConstraint-preserving QAOA formulation using Dicke state initialization and XY-mixer Hamiltonian for direct indexing portfolio optimization. Use when: implementing QAOA with hard cardinality constraints; designing constraint-preserving quantum ansatzes; mitigating barren plateaus via Trotterized initialization; comparing quantum vs classical portfolio optimization (SA, HRP); Direct Indexing with ESG constraints. Keywords: qaoa, xy-mixer, dicke state, portfolio optimization, constraint-preserv...Votes: 0GitHub stars: 3
- Oracle Gap And Signal Fidelity A Fixed Pool DiagnoDerived from arXiv:2607.17531 - Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time CollaborationVotes: 0GitHub stars: 3
- Optimal Photostimulation Selection For ConnectomicsOptimal photostimulation selection framework (OPhELIA) for efficient causal connectomics mapping using Bayesian experimental design. Enables reconstruction of exhaustive functional connectomes with minimal trials by combining Bayesian inference, active learning, and compressed sensing.Votes: 0GitHub stars: 3
- Novel Deep Neural Network Classifier Characterization Metrics With Applications To Dataless Evaluation**arXiv ID:** 2407.13000 **Authors:** Nathaniel Dean, Dilip Sarkar **Published:** 2024-07-17T20:40:46Z **Abstract:** The mainstream AI community has seen a rise in large-scale open-source classifiers, often pre-trained on vast datasets and tested on standard benchmarks; however, users facing diverse needs and limited, expensive test data may be overwhelmed by available choices. Deep Neural Network (DNN) classifiers undergo training, validation, and testing phases using example dataset, with t...Votes: 0GitHub stars: 3
- Mean Field Oscillatory Low Rank RnnMean-field theory for rich oscillatory dynamics in low-rank recurrent networks with activity-dependent adaptation. Analyzes how low-rank structure and adaptation interact to produce complex oscillatory and chaotic behavior in recurrent neural networks.Votes: 0GitHub stars: 3
- Information Coincidence IdentityInformation from coincidences — a single algebraic mixed coincidence identity that unifies information-theoretic variational results (Sanov, Chernoff, PAC-Bayes, Renyi). Use when deriving multi-prior information bounds, analyzing hypothesis testing error exponents, or building contrastive decoding frameworks.Votes: 0GitHub stars: 3
- Heaviside Continuity Of Rolling Coefficients For EDerived from arXiv:2607.04562 - Heaviside Continuity of Rolling Coefficients for Eliminating Epistemic Entropy in Large Language ModelsVotes: 0GitHub stars: 3
- Graphidyom Musical Expectation ModelingGraph-native Python reimplementation of the Information Dynamics of Music (IDyOM) model that represents predictive memories as explicit graph objects for musical expectation modeling and network analysis.Votes: 0GitHub stars: 3
- Free Probability Rnn Spectral AnalysisFree probability approach to analyzing stationary covariance spectra of random recurrent neural networks. Derives closed functional equations for moment generating functions of limiting stationary covariance spectra with random non-normal Gaussian weights.Votes: 0GitHub stars: 3
- Feynman Clock Error MitigationBBGKY-ISM quantum error mitigation using Feynman's clock Hamiltonian with polynomial overhead (arXiv: 2607.06752)Votes: 0GitHub stars: 3
- Coquasi Bialgebroids Cocycle TwistingCoquasi-bialgebroid theory over noncommutative base algebras using Takeuchi coalgebra formalism. Product associative up to invertible normalized 3-cocycle, with twisting theorem by convolution-invertible 2-cochains and Connes-Moscovici-type constructions.Votes: 0GitHub stars: 3
- Classifying Daily Activities Needs Posture Reconstructing Them Needs MotionSkill for understanding the dissociation between posture-based action classification and motion-dependent movement reconstruction in human visionVotes: 0GitHub stars: 3
- Cauchy Loss Function Robustness Under Gaussian And Cauchy Noise**arXiv ID:** 2302.07238 **Authors:** Thamsanqa Mlotshwa, Heinrich van Deventer, Anna Sergeevna Bosman **Published:** 2023-02-14T18:34:44Z **Abstract:** In supervised machine learning, the choice of loss function implicitly assumes a particular noise distribution over the data. For example, the frequently used mean squared error (MSE) loss assumes a Gaussian noise distribution. The choice of loss function during training and testing affects the performance of artificial neural networks (ANNs)...Votes: 0GitHub stars: 3
- Biophysical Hh Model Extracellular NeurostimulationLearning biophysical Hodgkin-Huxley models from extracellular MEA measurements using differentiable simulation and simulation-based inference. Enables precise neurostimulation prediction from minutes of recording instead of hours of stimulus testing.Votes: 0GitHub stars: 3
- Stress Testing Concept Erasure With Large LanguageDerived from arXiv:2607.17890 - Stress Testing Concept Erasure with Large Language Model AgentsVotes: 0GitHub stars: 3
- Llm As General VerifierLLM-as-a-Verifier general-purpose verification framework using probabilistic verification and multi-round self-correction for improving LLM output reliability across reasoning, coding, and mathematical tasks.Votes: 0GitHub stars: 3
- Llm As A VerifierGeneral-purpose verification framework using probabilistic logit expectation for continuous scoring, enabling multi-dimensional scaling of verification along granularity, repeated evaluation, and criteria decomposition.Votes: 0GitHub stars: 3
- Explicit Operator Ssm Neural OscillatorMathematical framework establishing explicit correspondence between state space models (S4/S4D) and exactly solvable nonlinear oscillator networks. Derives closed-form analytical operator for complete S4D forward propagation. Activation: state space model, S4, SSM, neural oscillator, sequence modeling, mathematical operator, computational neuroscience.Votes: 0GitHub stars: 3