:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Hammad, M. M.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.11090
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Comprehensive Survey of Complex-Valued Neural Networks: Insights into Backpropagation and Activation Functions
by: Hammad, M. M.
Published: (2024)

Artificial Neural Network and Deep Learning: Fundamentals and Theory
by: Hammad, M. M.
Published: (2024)

Adaptive Parametric Activation: Unifying and Generalising Activation Functions Across Tasks
by: Alexandridis, Konstantinos Panagiotis, et al.
Published: (2024)

Deep Learning-Based Metamodeling of Nonlinear Stochastic Dynamic Systems under Parametric and Predictive Uncertainty
by: Atila, Haimiti, et al.
Published: (2026)

Variational (Energy-Based) Spectral Learning: A Machine Learning Framework for Solving Partial Differential Equations
by: Hammad, M. M.
Published: (2026)

Smart Sampling: Self-Attention and Bootstrapping for Improved Ensembled Q-Learning
by: Khan, Muhammad Junaid, et al.
Published: (2024)

APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks
by: Subramanian, Barathi, et al.
Published: (2024)

Schrodinger Neural Network and Uncertainty Quantification: Quantum Machine
by: Hammad, M. M.
Published: (2025)

Stochastic Thermodynamics of Learning Parametric Probabilistic Models
by: Parsi, Shervin Sadat
Published: (2023)

Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence
by: Bonalli, Riccardo, et al.
Published: (2023)

Adaptive Rational Activations to Boost Deep Reinforcement Learning
by: Delfosse, Quentin, et al.
Published: (2021)

ReCA: A Parametric ReLU Composite Activation Function
by: Chidiac, John, et al.
Published: (2025)

Ensemble Deep Random Vector Functional Link Neural Network Based on Fuzzy Inference System
by: Sajid, M., et al.
Published: (2024)

Learning Expressive Random Feature Models via Parametrized Activations
by: Ma, Zailin, et al.
Published: (2024)

DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs
by: Shrestha, Aayam, et al.
Published: (2020)

TeLU Activation Function for Fast and Stable Deep Learning
by: Fernandez, Alfredo, et al.
Published: (2024)

Deep Learning with Parametric Lenses
by: Cruttwell, Geoffrey S. H., et al.
Published: (2024)

ANAct: Adaptive Normalization for Activation Functions
by: Peiwen, Yuan, et al.
Published: (2022)

Emergence of Globally Attracting Fixed Points in Deep Neural Networks With Nonlinear Activations
by: Joudaki, Amir, et al.
Published: (2024)

Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertising
by: Yang, Shuai, et al.
Published: (2024)

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
by: Surendran, Sobihan, et al.
Published: (2024)

DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
by: Mantri, Krishna Sri Ipsit, et al.
Published: (2024)

Parametrized Multi-Agent Routing via Deep Attention Models
by: Basiri, Salar, et al.
Published: (2025)

Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes
by: Wu, Bohan, et al.
Published: (2024)

Adaptive Activation Functions for Predictive Modeling with Sparse Experimental Data
by: Pourkamali-Anaraki, Farhad, et al.
Published: (2024)

Stochastic Voronoi Ensembles for Anomaly Detection
by: Cao, Yang, et al.
Published: (2026)

Boosting Deep Ensembles with Learning Rate Tuning
by: Jin, Hongpeng, et al.
Published: (2024)

Deep Eigenspace Network for Parametric Non-self-adjoint Eigenvalue Problems
by: Li, H., et al.
Published: (2025)

Optimal Kernel Tuning Parameter Prediction using Deep Sequence Models
by: Mahmood, Khawir, et al.
Published: (2024)

Non-Parametric Rehearsal Learning via Conditional Mean Embeddings
by: Du, Wen-Bo, et al.
Published: (2026)

Adaptive Ensemble Learning with Gaussian Copula for Load Forecasting
by: Yang, Junying, et al.
Published: (2025)

The Parametric Complexity of Operator Learning
by: Lanthaler, Samuel, et al.
Published: (2023)

Unsupervised Video Continual Learning via Non-Parametric Deep Embedded Clustering
by: Kurpukdee, Nattapong, et al.
Published: (2025)

Ensembles of Neural Surrogates for Parametric Sensitivity in Ocean Modeling
by: Sun, Yixuan, et al.
Published: (2025)

Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
by: Waxman, Daniel, et al.
Published: (2024)

Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
by: Leão, Dorival, et al.
Published: (2026)

Ensemble and Mixture-of-Experts DeepONets For Operator Learning
by: Sharma, Ramansh, et al.
Published: (2024)

Evaluating Artificial Intelligence Algorithms for the Standardization of Transtibial Prosthetic Socket Shape Design
by: Jordaan, C. H. E., et al.
Published: (2025)

Deep Multivariate Models with Parametric Conditionals
by: Schlesinger, Dmitrij, et al.
Published: (2026)

Efficiently Training Deep-Learning Parametric Policies using Lagrangian Duality
by: Rosemberg, Andrew, et al.
Published: (2024)