GLENS uses diffusion models on solver iterates to generate high-quality and diverse initial guesses for multimodal non-convex optimization, leading to faster solver convergence.
hub
Alimitedmem- ory algorithm for bound constrained optimization
22 Pith papers cite this work, alongside 4,852 external citations. Polarity classification is still indexing.
22
Pith papers citing it
4,852
external citations · Crossref
hub tools
citation-role summary
background 1
baseline 1
method 1
citation-polarity summary
representative citing papers
Complete MUB ensembles are optimal for isotropic Gaussian random-Hamiltonian width among d+1 basis unions, and adaptive MUB-XRot QAOA is non-worse than standard QAOA in 80% of 1500 benchmark cases across MaxCut, MIS, and knapsack.
Leaky integrator RNNs with adaptive time constants switch between four frequency bands using multiple mechanisms including subpopulation turnover, baseline shifts, and phase reorganization, with high frequencies dominated by short-time-constant neurons.
DualTCN is the first deep-learning model for time-domain marine CSEM inversion that regresses four earth parameters, achieves high accuracy on simulated data, and runs up to 21,000 times faster than classical optimizers.
Variational optimization on dipolar spin chains reaches 0.92 of the quantum Fisher information benchmark for joint magnetometry and gradiometry, delivering a 4.2x advantage over the standard quantum limit.
BERT stores relational knowledge extractable via cloze queries without fine-tuning and matches supervised baselines on open-domain QA tasks.
A VSS-based joint FWI framework enables direct multi-deployment inversion of geophone and DAS data, yielding more accurate elastic parameter recovery than single-sensor cases on Marmousi benchmarks when sensors provide complementary information.
Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
RepNN reparameterizes the first hidden layer of DNNs to enable adaptive frequency scaling, improving accuracy on oscillatory and multiscale functions with minimal extra cost.
A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.
LLMs show partial internal coherence in medical decisions but frequently fail to accurately report their preferences or adopt user-directed ones via prompting.
GJ 1132 b is estimated to have received at least 50 times the cumulative XUV flux of modern Earth with over 95% probability across models, supporting its classification as an atmosphere-free world.
Helmlab defines MetricSpace and GenSpace as analytical data-driven color spaces that cut color difference error by 23% versus CIEDE2000 on primary benchmarks while outperforming OKLab on gradient tasks.
A photoacoustic beacon in the needle bevel allows real-time 3D ultrasonic tracking with sub-2 mm accuracy in water and tissue phantoms, cutting biopsy failure rates by 35% in a clinician usability study.
An adaptive damping and DIIS protocol stabilizes QmDFT embedding with hybrid functionals on 10 PAHs, yielding LDA agreement with FCI for ground states and B3LYP agreement with experimental gaps while bypassing explicit excited-state computations.
A robust Riemannian Levenberg-Marquardt algorithm is formulated in block-wise form, with convergence results carried over from prior work and demonstrated via an open-source Manopt.jl implementation on tasks including geodesic regression and Procrustes analysis.
A shooting technique yields smooth control pulses for quantum gates on spin qudits that are faster than GRAPE, with the advantage growing as system dimension increases, shown in numerical simulations inspired by single molecule magnets.
By augmenting quantum circuit ansatze with optimized swap networks, the work achieves better performance in ground-state energy calculations using fewer resources on devices with arbitrary qubit connectivity.
PISP projects high-dimensional spectra into optimized subspaces using PCA or active subspaces plus L1 selection to raise accuracy and speed of stellar parameter inference over standard methods.
An open-source Jax-based SPH simulator generates training data for LPV state-space surrogates that approximate fuel sloshing dynamics and enable 100x faster closed-loop spacecraft simulations under zero gravity.
Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.
SciPy 1.0 documents a mature open-source library that has become the de facto standard for scientific algorithms in Python with broad adoption across research projects.
citing papers explorer
-
Data-driven Learning of LPV Surrogate Models of Fuel Sloshing
An open-source Jax-based SPH simulator generates training data for LPV state-space surrogates that approximate fuel sloshing dynamics and enable 100x faster closed-loop spacecraft simulations under zero gravity.