Results 81 to 90 of about 4,805,610 (298)
Multi-objective turbomachinery optimization using a gradient-enhanced multi-layer perceptron
Response surface models (RSMs) have found widespread use to reduce the overall computational cost of turbomachinery blading design optimization. Recent developments have seen the successful use of gradient information alongside sampled response values in
Duta, Mihaela, Duta, MC, Duta, MD
core +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Intrinsic Plasticity Based Inference Acceleration for Spiking Multi-Layer Perceptron
Intrinsic plasticity (IP) mechanism was originally found in the biological neuron as a membrane potential adaptive tuning scheme, which was used to change the connection strength between neurons, so that animal brain had the ability to learn or store ...
Shuxun Zhang +3 more
doaj +1 more source
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen +12 more
wiley +1 more source
A Target Tracking Method Based on a Pyramid Channel Attention Mechanism
To enhance the tracking performance of transformer-based trackers in complex scenes, we propose a novel visual object tracking method that incorporates three key components: a pyramid channel attention mechanism, a hierarchical cross-attention structure,
Dongxuan Zhao +5 more
doaj +1 more source
Multi-layer Perceptron on Interval Data [PDF]
We study in this paper several methods that allow one to use interval data as inputs for Multi-layer Perceptrons. We show that interesting results can be obtained by using together two methods: the extremal values method which is based on a complete description of intervals, and the simulation method which is based on a probabilistic understanding of ...
Fabrice Rossi, Brieuc Conan-Guez
openaire +1 more source
Enhanced Ionic Conductivity at the Solid Electrolyte Interphase of Oxygen‐Doped Li6PS5Cl
Machine‐learned molecular dynamics and machine‐learning‐based phase identification reveal the kinetically formed SEI at buried Li | Li6PS5Cl interfaces. The SEI is dominated by Li2S‐based anion‐substituted phases, while oxygen doping enhances SEI ionic conductivity.
Sojeong Yang +6 more
wiley +1 more source
Modeling of the nonlinear flame response of a Bunsen-type flame via multi-layer perceptron
Multi-layer perceptron; Flame describing function; Laminar premixed flame; Self-excited thermoacoustic oscillations; Neural ...
Nilam Tathawadekar a , d , ∗, Nguyen Anh Khoa Doan b , c , Camilo F. Silva b , Nils Thuerey d
core +1 more source
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu +9 more
wiley +1 more source
CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su +5 more
wiley +1 more source

