diffusion models

TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation

TNFR-Python-Engine is a Python framework for coherent-pattern analysis on graph-coupled networks. The nodal relation dEPI/dt = nu_f DeltaNFR organizes a declared evolution model; pressure, phase, capacity, support and any additional forcing require their own specifications. The engine provides 13 registered structural...

Identifying Memorization of Diffusion Models through p-Laplace Analysis: Estimators, Bounds and Applications

Quantum Fractional Dynamics in Disordered Semiconductor Networks

Classical diffusion models governed by Fick's Second Law rely strictly on integer-order temporal derivatives and the central limit theorem, leading to standard Gaussian particle spatial profiles. However, transport processes operating within disordered quantum networks, multi-qubit semiconductor topologies, and turbule...

Quantum Fractional Dynamics in Disordered Semiconductor Networks

Classical diffusion models governed by Fick's Second Law rely strictly on integer-order temporal derivatives and the central limit theorem, leading to standard Gaussian particle spatial profiles. However, transport processes operating within disordered quantum networks, multi-qubit semiconductor topologies, and turbule...

Replication Data for the manuscript: Adjoint-State Identifiability of Piezo-Tunable Valley Splitting in 2D Magnetic Heterostructures

Title: Replication Data for: Adjoint-State Identifiability of Piezo-Tunable Valley Splitting in 2D Magnetic Heterostructures Description: This repository contains the complete multiscale computational framework and dataset required to reproduce the findings in the manuscript "Adjoint-State Identifiability of Piezo-Tuna...

Replication Data for the manuscript: Adjoint-State Identifiability of Piezo-Tunable Valley Splitting in 2D Magnetic Heterostructures

Title: Replication Data for: Adjoint-State Identifiability of Piezo-Tunable Valley Splitting in 2D Magnetic Heterostructures Description: This repository contains the complete multiscale computational framework and dataset required to reproduce the findings in the manuscript "Adjoint-State Identifiability of Piezo-Tuna...

Comparative Machine Learning and Graph Neural Network Approaches for Blood-Brain Barrier Permeability Prediction

Versioned research release of the BBB permeability prediction project. This release preserves the complete source code, experimental results, documentation, figures, and reproducibility materials for the project. Contents: Phase 3: 5-fold scaffold CV classical ML (RF AUROC 0.921+/-0.024) Phase 4: Chemprop GNN ensemble...

Comparative Machine Learning and Graph Neural Network Approaches for Blood-Brain Barrier Permeability Prediction

Versioned research release of the BBB permeability prediction project. This release preserves the complete source code, experimental results, documentation, figures, and reproducibility materials for the project. Contents: Phase 3: 5-fold scaffold CV classical ML (RF AUROC 0.921+/-0.024) Phase 4: Chemprop GNN ensemble...

DTI-Guided Volumetric Spherical Harmonics Regression for Single-to-Multi-Shell dMRI Synthesis

DTI-SHNet is proposed, a single-to-multi-shell synthesis framework that operates in the real symmetric spherical harmonics (SH) coefficient domain and performs spatially aware volumetric regression and introduces a signal consistency regularization that reconstructs signals on randomly sampled canonical directions from...

Toward Bimanual Dexterous Grasp of Partially Observable Objects With Data Synthesis and Diffusion-Based Generation Approach

Data-driven bimanual dexterous grasping remains challenging due to the lack of large-scale physically valid datasets and the difficulty of generating feasible bimanual grasps from partial observations. We propose an efficient bimanual grasp synthesis pipeline that decouples bimanual grasp generation into single-hand gr...

Beyond Diffusion: A hybrid mechanistic modeling approach to accurate wax deposition prediction

Tissue Channel Modeling with Molecular Communication Simulations and Testbed

This work-in-progress (WIP) paper investigates biological tissue as a communication channel for molecular communication (MC) systems. Existing MC models typically assume simplified diffusion environments, whereas biomedical applications such as HIV reservoir detection and cancer localization require molecular signals t...