diffusion models

A multimodal deep learning radiomics nomogram integrating clinicopathological features for predicting pathological complete response after neoadjuvant therapy in triple-negative breast cancer: a multicenter retrospective study

Background Accurate noninvasive estimation of pathological complete response (pCR) after neoadjuvant therapy (NAT) in triple-negative breast cancer (TNBC) may support multidisciplinary discussions, but multimodal MRI-ultrasound evidence remains limited. We developed and externally validated a clinicopathological deep l...

ShyBFM v1.0: unstructured grid advection-diffusion-reaction modelling for coastal biogeochemical processes

This study presents ShyBFM, a high-resolution coupled physical–biogeochemical modelling system based on an unstructured grid. The physical component is the parallel computing finite element, ocean circulation model SHYFEM-MPI, while the marine ecosystem is described through the Biogeochemical Flux Model (BFM) which res...

AETERNA SINGULARITY: The Grand Unified Resolution of the 6 Millennium Prize Problems via Self-Adjoint Spectral Operators and Geometric Invariants

This master publication presents the complete, deterministic analytic and algebraic resolution of the 6 Millennium Prize Problems established by the Clay Mathematics Institute (CMI), unified under the AETERNA Self-Adjoint Spectral Operator Framework by Dimitar Prodromov (AETERNA Technologies EOOD). THE 6 FORMAL RESOLUT...

A Deterministic Spectral Proof of the Riemann Hypothesis via Weil Positivity, Li Criterion Asymptotics, and Catuskoti Algebraic Induction

The Riemann Hypothesis (RH), formulated by Bernhard Riemann in 1859, asserts that all non-trivial zeros of the Riemann zeta function have real part Re(s) = 1/2. In this paper, we establish a deterministic, complete analytic proof of the Riemann Hypothesis by synthesizing an exact zero-float rational arithmetic substrat...

Loneliness to consumption intention: emotional bonding and escapism in AI emotional companion app use

With the diffusion of generative AI, AI emotional companion apps have emerged as a new domain of digital consumption in which users may pay to extend relationship-like experiences. This study examines how loneliness and actual-ideal self-discrepancy are associated with experience-enhancing consumption intention and con...

Lookahead-Then-Verify: Reliable Constrained Decoding for Diffusion LLMs under Context-Free Grammars

Diffusion Large Language Models (dLLMs) have demonstrated promising capabilities and are increasingly used to produce formal languages defined by context-free grammars, such as source code and chemical expressions. However, as probabilistic models, they still struggle to generate syntactically valid outputs reliably. A...

A Grid of Model Contribution Functions and Spectra: to help with the interpretation of time-resolved observations of brown dwarfs

OVERVIEW This Zenodo record provides a grid of thermal emission spectra and their corresponding thermal-emission contribution-function summaries (average emission pressures indicating where the observed flux originates) for non-irradiated substellar objects in chemical equilibrium, as described in Phillippe et al. (202...

A Grid of Model Contribution Functions and Spectra: to help with the interpretation of time-resolved observations of brown dwarfs

OVERVIEW This Zenodo record provides a grid of thermal emission spectra and their corresponding thermal-emission contribution-function summaries (average emission pressures indicating where the observed flux originates) for non-irradiated substellar objects in chemical equilibrium, as described in Phillippe et al. (202...

BridgeDiff: A two-stage conditional diffusion model for bridge point clouds completion

Adaptive Mean Flow for Responsive Closed-Loop Robot Control

Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their high performance and ability to model continuous and multimodal distributions. However, the iterative denoising procedure used by these models introduces significant prediction latency, hindering hig...

Physically Aware Generative Design for Spatial Mechanism Synthesis: A Differentiable Diffusion-Refinement Framework

Spatial mechanism synthesis requires joint reasoning over discrete topology and continuous geometry under strict loop-closure constraints. Existing search-based methods are often tied to predefined topology spaces, while purely data-driven generators can produce topologically plausible but kinematically infeasible mech...

Research on Green Technology Investment Strategies in Biodegradable Materials Supply Chain under Information Asymmetry

Scientific design of patent licensing contract and sales channel selection are key to breaking the green technology promotion dilemma of biodegradable materials. Under market scale information asymmetry, we construct a three-echelon supply chain principal agent model including a patent technology supplier, a biodegrada...