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https://openreview.net/forum?id=1piyfD_ictW On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data | OpenReview It has been empirically observed that training large models with weighted cross-entropy (CE) beyond the zero-training-error regime is not a satisfactory remedy... https://openreview.net/forum?id=0ksNeD1SJT Scaling Exponents Across Parameterizations and Optimizers | OpenReview Robust and effective scaling of models from small to large width typically requires the precise adjustment of many algorithmic and architectural details, such... scaling exponents across parameterizations optimizers https://deepai.org/publication/training-integrable-parameterizations-of-deep-neural-networks-in-the-infinite-width-limit Training Integrable Parameterizations of Deep Neural Networks in the Infinite-Width Limit | DeepAI Oct 29, 2021 - 10/29/21 - To theoretically understand the behavior of trained deep neural networks, it is necessary to study the dynamics induced by gradien... deep neural networks https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2023.1127345/full Frontiers | Parameterizations of immiscible two-phase flow in porous media A fundamental variable characterizing immiscible two-phase flow in porous media is the wetting saturation, which is the ratio between the pore volume fille... two phase flow frontiers parameterizations immiscible porous https://www.mathworks.com/help/slcontrol/ug/sltuner.showtunable.html showTunable - Show value of parameterizations of tunable blocks of slTuner interface - MATLAB This MATLAB function displays the values of the parametric models associated with each tunable block in the slTuner interface, st. show value parameterizations blocks interface https://www.pnnl.gov/publications/regional-scale-modeling-parameterizations-secondary-organic-aerosol-formation-isoprene Regional-scale modeling parameterizations for secondary organic aerosol formation from isoprene... secondary organic aerosol scale modeling regional parameterizations https://www.metoffice.gov.uk/research/weather/atmospheric-dispersion/dispersion-processes Dispersion processes and parameterizations - Met Office Researching turbulent dispersion and improving its representation in the Met Office's atmospheric dispersion model. dispersion processes parameterizations office https://arxiv.org/abs/0909.5674 [0909.5674] A model problem for conformal parameterizations of the Einstein constraint equations Abstract page for arXiv paper 0909.5674: A model problem for conformal parameterizations of the Einstein constraint equations https://arxiv.org/abs/1310.4915v1 [1310.4915v1] Fitting ideals and multiple-points of surface parameterizations Abstract page for arXiv paper 1310.4915v1: Fitting ideals and multiple-points of surface parameterizations 1310 fitting ideals multiple points https://www.southampton.ac.uk/courses/2029-30/modules/feeg6009 Design Search and Optimisation (DSO) - Principles, Methods, Parameterizations and Case Studies |... This module introduces students to formal design search and optimization (DSO) approaches using a mixture of lectures covering theory and practice and a series... design search optimisation dso principles methods https://www.southampton.ac.uk/courses/2025-26/modules/feeg6009 Design Search and Optimisation (DSO) - Principles, Methods, Parameterizations and Case Studies |... This module introduces students to formal design search and optimization (DSO) approaches using a mixture of lectures covering theory and practice and a series... design search optimisation dso principles methods https://www.southampton.ac.uk/courses/2028-29/modules/feeg6009 Design Search and Optimisation (DSO) - Principles, Methods, Parameterizations and Case Studies |... This module introduces students to formal design search and optimization (DSO) approaches using a mixture of lectures covering theory and practice and a series... design search optimisation dso principles methods https://openreview.net/forum?id=h15RyEj151 Provable Benefits of Complex Parameterizations for Structured State Space Models | OpenReview Structured state space models (SSMs), the core engine behind prominent neural networks such as S4 and Mamba, are linear dynamical systems adhering to a... state space models benefits of provable complex parameterizations https://deepai.org/publication/alternative-function-approximation-parameterizations-for-solving-games-an-analysis-of-f-regression-counterfactual-regret-minimization Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression... Dec 6, 2019 - 12/06/19 - Function approximation is a powerful approach for structuring large decision problems that has facilitated great achievements in t... function approximation