26 papers · ranked by Valyu relevance
Joan Vendrell Gallart, Russell Bent, Solmaz S. Kia
This paper considers an optimal radial reconfiguration problem in multi-source distribution networks, where the goal is to find a radial configuration that minimizes quadratic distribution costs while ensuring all sink demands are met. This problem arises in critical infrastructure systems such as power distribution…
Salar Beigzad
—The Forward-Forward algorithm eliminates backpropagation's memory constraints and biological implausibility through dual forward passes with positive and negative data. However, conventional implementations suffer from critical interlayer isolation, where layers optimize goodness functions independently without…
Gallart, Joan Vendrell, Bent, Russell + 2 more
— Microgrids offer a promising paradigm for integrating distributed energy resources, bolstering energy resilience, and reducing the impact of blackouts. However, their inherent decentralization and dynamic operation present substantial energy management complexities. These complexities, including balancing supply and…
Arya Shah, Vaibhav Tripathi
The Forward-Forward (FF) algorithm offers a biologically plausible alternative to backpropagation, enabling neural networks to learn through local updates. However, FF's efficacy relies heavily on the definition of "goodness", which is a scalar measure of neural activity. While current implementations predominantly…
Sudipto Banerjee, Xiang Chen, Ian Frankenburg, Daniel Zhou
Models Authors: Sudipto Banerjee, Xiang Chen, Ian Frankenburg, Daniel Zhou We develop an approach for Bayesian learning of spatiotemporal dynamical mechanistic models. Such learning consists of statistical emulation of the mechanistic system that can efficiently interpolate the output of the system from arbitrary…
Florian Ingels, Léa Vandamme, Mathilde Girard, Clément Agret + 2 more
Modern sequencing continues to drive explosive growth of nucleotide sequence archives, pushing MinHash-derived sketching methods to their practical scalability limits. State-of-the-art tools such as Mash, Dashing2, and Bindash2 provide compact sketches and accurate similarity estimates for large collections, yet…
Robert M. Raddi, Tim Marshall, Vincent A. Voelz
To quantify how well theoretical predictions of structural ensembles agree with experimental measurements, we depend on the accuracy of forward models (FMs). These models are computational frameworks that generate observable quantities from molecular configurations based on empirical relationships linking specific…
Yong Yang, Daying Sun, Zhiyuan Ma, Wenhua Gu + 1 more
The gravity forward modeling algorithm is a compute-intensive method and is widely used in scientific computing, particularly in geophysics, to predict the impact of subsurface structures on surface gravity fields. Traditional implementations rely on CPUs, where performance gains are mainly achieved through algorithmic…
Na Che, Xianwei Zeng, Jian Zhao, Haiyan Wang + 2 more
Aiming at the problems of large search space, unstable computational efficiency, and lack of safety of generated paths in complex environments of traditional HybridA algorithms, this paper proposes an improved HybridA algorithm based on Voronoi diagrams and safe corridors (GCHybridA) to overcome these challenges. The…
Albert Jiménez-Blanco, Lorién López-Villellas, Juan Carlos Moure, Miquel Moreto + 1 more
Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long…
Uwaise Ibna Islam, Davide Cozzi, Travis Gagie, Rahul Varki + 4 more
Large, phase-resolved haplotype panels—now emerging from efforts such as UK Biobank, TOPMed, All of Us, and the Mexican Biobank—enable fine-grained analyses of admixture, local ancestry, and imputation. The Positional Burrows–Wheeler Transform (PBWT) is a natural index for these data, supporting efficient phase-aware…
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
MaxFlow is a fundamental problem in graph theory and combinatorial optimisation, used to determine the maximum flow from a source node to a sink node in a flow network. It finds applications in diverse domains, including computer networks, transportation, and image segmentation. The core idea is to maximise the total…
Benjamin Lieser, Georgy Belousov, Johannes Söding
Background Most popular tools for reconstructing phylogenetic trees from multiple sequence alignments use a model of molecular evolution in which a single substitution matrix or a small set of fixed matrices are shared between all columns. Models with column-specific rate matrices can in principle be fit by automatic…
Dimitry Tegunov
Fourier-space projection operations are central to electron microscopy single-particle analysis and electron tomography algorithms. Machine learning methods require differentiable implementations for end-to-end model training, but PyTorch’s built-in operations are too slow for practical use. This paper introduces…
Authors not listed
Transition state (TS) geometries of chemical reactions are key to understanding reaction mechanisms and estimating kinetic properties. Inferring these directly from 2D reaction graphs offers chemists a powerful tool for rapid and accessible reaction analysis. Quantum chemical methods for computing TSs are…
Liyun Su, Linke Hou, Jiaodi Liu, Jyotindra Narayan
Stewart platforms are widely used in flight simulators, precision machining, and other fields due to their advantages in high precision, high dynamic response, and full six-degree-of-freedom spatial motion. However, the positioning accuracy of traditional rigid Stewart platforms is difficult to further improve due to…
Ismail Melik Turker, Isa Yildirim
The per-cell quantities are the base coefficients , the per-slice shifts , and the normalization coefficient . The base coefficients are the values of from ((170-3)$22$) evaluated on the first slice () for each detector cell. The shifts are the per-voxel changes in along the slice axis, constant across slices for each…
Jie Gao, Weinan Xie, Haoya Liu, Junda Zhou + 3 more
Multi-AGV (Automated Guided Vehicle) systems operating in complex warehouse environments equipped with movable containers encounter several challenges, including high system no-load rate, low task response efficiency, and imbalanced path utilization. To address these issues, we propose an integrated optimization…
Francesco Donnarumma, Thomas Parr, Karl Friston, James Whittington + 1 more
How the brain plans and maintains sequences of future actions remains a central question in systems neuroscience. Recent studies in the frontal cortex have revealed that multiple elements of a sequence are represented simultaneously in separable neural subspaces, challenging classical serial models of sequential…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
The Maximum Flow (Max-Flow) problem is a cornerstone in graph theory and combinatorial optimization, aiming to determine the largest possible flow from a designated source node to a sink node within a capacitated flow network. It has extensive applications across diverse domains such as computer networking…
Authors not listed
Atomistic simulations provide essential mechanistic insights into chemical processes, yet many important phenomena in chemistry and materials science occur on timescales that are inaccessible to molecular dynamics. Existing computational approaches force a choice between atomic resolution on relatively short timescales…
Abhijeet Sahu, Harmit Singh, Soham Nandy, G. Ramakrishna
Spanning trees are fundamental structures in graph theory, essential for various applications such as network maintenance, routing adjustments, and many more. The dynamic nature of real-world networks requires efficient updates to these structures as the underlying graph evolves. Maintaining rooted spanning trees…
Davide Noè, Hideaki Yamamoto, Yuichi Katori, Shigeo Sato
The predictive coding framework offers a compelling model for temporal signal processing in the cortex. Recent studies explored its implementation in spiking architectures using Hebbian plasticity rules or offline learning; however, a biologically inspired model that enables gradient-based minimization of prediction…
Authors not listed
A multi-fidelity Monte Carlo framework for molecular dynamics simulations of the diffusion coefficient of liquid water is presented. The model hierarchy is constructed based on the size of the simulation box, taking advantage of the well-known size effects that simulations of the diffusion coefficient suffer from.…
Authors not listed
The Hidden Subgroup Problem (HSP) unifies several landmark quantum algorithms, yet systematic exploration of its variants and modern applications has slowed. This paper revives HSP-based algorithm design by examining new group structures with direct relevance to post-quantum cryptography, lattice problems, and…