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Tag: framework

  • Constrained Density Estimation via Optimal Transport

    Constrained Density Estimation via Optimal Transport arXiv:2601.06830v1 Announce Type: new Abstract: A novel framework for density estimation under expectation constraints is proposed. The framework minimizes the Wasserstein distance between the estimated density and a prior, subject to the constraints that the expected value of a set of functions adopts or exceeds given values. The framework…

  • Towards a unified framework for guided diffusion models

    Towards a unified framework for guided diffusion models arXiv:2512.04985v1 Announce Type: new Abstract: Guided or controlled data generation with diffusion modelsblfootnote{Partial preliminary results of this work appeared in International Conference on Machine Learning 2025 citep{li2025provable}.} has become a cornerstone of modern generative modeling. Despite substantial advances in diffusion model theory, the theoretical understanding of guided…

  • The Power of Framework Dimensions: What Data Scientists Should Know

    The Power of Framework Dimensions: What Data Scientists Should Know Practical guidance and a case study The post The Power of Framework Dimensions: What Data Scientists Should Know appeared first on Towards Data Science. Chinmay Kakatkar Go to original source

  • A unified Bayesian framework for adversarial robustness

    A unified Bayesian framework for adversarial robustness arXiv:2510.09288v1 Announce Type: new Abstract: The vulnerability of machine learning models to adversarial attacks remains a critical security challenge. Traditional defenses, such as adversarial training, typically robustify models by minimizing a worst-case loss. However, these deterministic approaches do not account for uncertainty in the adversary’s attack. While stochastic…

  • Field of View Enhanced Signal Dependent Binauralization with Mixture of Experts Framework for Continuous Source Motion

    Field of View Enhanced Signal Dependent Binauralization with Mixture of Experts Framework for Continuous Source Motion arXiv:2509.13548v1 Announce Type: cross Abstract: We propose a novel mixture of experts framework for field-of-view enhancement in binaural signal matching. Our approach enables dynamic spatial audio rendering that adapts to continuous talker motion, allowing users to emphasize or suppress…

  • Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning

    Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning arXiv:2509.11070v1 Announce Type: new Abstract: We develop a stochastic approximation framework for learning nonlinear operators between infinite-dimensional spaces utilizing general Mercer operator-valued kernels. Our framework encompasses two key classes: (i) compact kernels, which admit discrete spectral decompositions, and (ii) diagonal kernels of the form $K(x,x’)=k(x,x’)T$, where $k$…

  • Coconut: A Framework for Latent Reasoning in LLMs

    Coconut: A Framework for Latent Reasoning in LLMs Explaining Coconut (Training Large Language Models to Reason in a Continuous Latent Space) in simple terms The post Coconut: A Framework for Latent Reasoning in LLMs appeared first on Towards Data Science. Youssef Farag Go to original source

  • The Stanford Framework That Turns AI into Your PM Superpower

    The Stanford Framework That Turns AI into Your PM Superpower A human-centric guide to AI automation for product managers. The post The Stanford Framework That Turns AI into Your PM Superpower appeared first on Towards Data Science. Rahul Vir Go to original source

  • A Transfer Learning Framework for Multilayer Networks via Model Averaging

    A Transfer Learning Framework for Multilayer Networks via Model Averaging arXiv:2506.12455v1 Announce Type: new Abstract: Link prediction in multilayer networks is a key challenge in applications such as recommendation systems and protein-protein interaction prediction. While many techniques have been developed, most rely on assumptions about shared structures and require access to raw auxiliary data, limiting…

  • A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example

    A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example arXiv:2505.03177v1 Announce Type: new Abstract: Bioprocess mechanistic modeling is essential for advancing intelligent digital twin representation of biomanufacturing, yet challenges persist due to complex intracellular regulation, stochastic system behavior, and limited experimental data. This paper introduces a symbolic and statistical learning…

  • A Statistical Framework for Ranking LLM-Based Chatbots

    A Statistical Framework for Ranking LLM-Based Chatbots arXiv:2412.18407v1 Announce Type: new Abstract: Large language models (LLMs) have transformed natural language processing, with frameworks like Chatbot Arena providing pioneering platforms for evaluating these models. By facilitating millions of pairwise comparisons based on human judgments, Chatbot Arena has become a cornerstone in LLM evaluation, offering rich datasets…