:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Dakurah, Sixtus
Format:	Preprint
Published:	2025
Subjects:	Quantitative Methods Computational Geometry Machine Learning
Online Access:	https://arxiv.org/abs/2512.12974
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spanning Tree Basis for Unbiased Averaging of Network Topologies
by: Dakurah, Sixtus
Published: (2025)

Brain Networks Flow-Topology via Variance Minimization in the Wasserstein Space
by: Dakurah, Sixtus
Published: (2025)

Discrete Heat Kernels on Simplicial Complexes and Its Application to Functional Brain Networks
by: Dakurah, Sixtus
Published: (2025)

TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration
by: Wang, Qipeng, et al.
Published: (2025)

Data Valuation with Gradient Similarity
by: Evans, Nathaniel J., et al.
Published: (2024)

Data-Dependent Smoothing for Protein Discovery with Walk-Jump Sampling
by: Anumasa, Srinivas, et al.
Published: (2025)

Transition Path Sampling with Boltzmann Generator-based MCMC Moves
by: Plainer, Michael, et al.
Published: (2023)

Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples
by: Sanchez-Fernandez, Ana, et al.
Published: (2026)

Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths
by: Wang, Yueyang, et al.
Published: (2025)

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction
by: Muna, Ummay Maria, et al.
Published: (2025)

A Subsequence Approach to Topological Data Analysis for Irregularly-Spaced Time Series
by: Dakurah, Sixtus, et al.
Published: (2024)

Reward-Guided Discrete Diffusion via Clean-Sample Markov Chain for Molecule and Biological Sequence Design
by: Phunyaphibarn, Prin, et al.
Published: (2026)

Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability
by: Pinheiro, João Manoel Herrera, et al.
Published: (2024)

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
by: Li, Xuan, et al.
Published: (2023)

Transformers for molecular property prediction: Lessons learned from the past five years
by: Sultan, Afnan, et al.
Published: (2024)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models
by: Kulytė, Paulina, et al.
Published: (2024)

Impact of automatic speech recognition quality on Alzheimer's disease detection from spontaneous speech: a reproducible benchmark study with lexical modeling and statistical validation
by: Samanta, Himadri S
Published: (2026)

Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations
by: Lu, Jiarui, et al.
Published: (2024)

Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives
by: Liu, Xiaokun, et al.
Published: (2025)

Planar morphometry via functional shape data analysis and quasi-conformal mappings
by: Li, Hangyu, et al.
Published: (2026)

ImmunoAI: Accelerated Antibody Discovery Using Gradient-Boosted Machine Learning with Thermodynamic-Hydrodynamic Descriptors and 3D Geometric Interface Topology
by: Shivakumar, Shawnak, et al.
Published: (2025)

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling
by: Lu, Jiarui, et al.
Published: (2023)

Enabling Few-Shot Alzheimer's Disease Diagnosis on Biomarker Data with Tabular LLMs
by: Kearney, Sophie, et al.
Published: (2025)

Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations
by: Qi, Cong, et al.
Published: (2025)

Integrating Single-Cell Foundation Models with Graph Neural Networks for Drug Response Prediction
by: Rossner, Till, et al.
Published: (2025)

A Novel Recurrent Neural Network Framework for Prediction and Treatment of Oncogenic Mutation Progression
by: Parthasarathy, Rishab, et al.
Published: (2025)

A Systematic Review on the Generative AI Applications in Human Medical Genomics
by: Changalidis, Anton, et al.
Published: (2025)

Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Methods: A Retrospective Cohort Study
by: An, Mary E., et al.
Published: (2025)

Devising a solution to the problems of Cancer awareness in Telangana
by: Avhad, Priyanka, et al.
Published: (2025)

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins
by: Tan, Yang, et al.
Published: (2025)

Statistical NLP for Optimization of Clinical Trial Success Prediction in Pharmaceutical R&D
by: Doane, Michael R.
Published: (2025)

Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
by: Han, Yuchen, et al.
Published: (2025)

Rep3Net: An Approach Exploiting Multimodal Representation for Molecular Bioactivity Prediction
by: Islam, Sabrina, et al.
Published: (2025)

Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration
by: Murden, Raphiel J., et al.
Published: (2026)

HIGHT: Hierarchical Graph Tokenization for Molecule-Language Alignment
by: Chen, Yongqiang, et al.
Published: (2024)

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment
by: Soukarieh, Inass, et al.
Published: (2024)

Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries
by: Zhou, Liqi, et al.
Published: (2026)

Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases
by: Yang, Yumeng, et al.
Published: (2024)

MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
by: Li, Jiatong, et al.
Published: (2024)

Geometric Stability: The Missing Axis of Representations
by: Raju, Prashant C.
Published: (2026)