How important are activation functions in regression and classification? A survey, performance comparison, and future directions

6 September 2022

Papers citing "How important are activation functions in regression and classification? A survey, performance comparison, and future directions"

27 / 27 papers shown

Title
Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs Sidharth S. Menon Ameya D. Jagtap PINN 139 0 0 06 May 2025
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild Damien Teney Liangze Jiang Florin Gogianu Ehsan Abbasnejad 169 0 0 13 Mar 2025
Kolmogorov-Arnold Networks in Low-Data Regimes: A Comparative Study with Multilayer Perceptrons Farhad Pourkamali-Anaraki 35 5 0 16 Sep 2024
Back to the Continuous Attractor Ábel Ságodi Guillermo Martín-Sánchez Piotr Sokól Il Memming Park 30 2 0 31 Jul 2024
Can all variations within the unified mask-based beamformer framework achieve identical peak extraction performance? Atsuo Hiroe Katsutoshi Itoyama Kazuhiro Nakadai 37 0 0 22 Jul 2024
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions Alireza Afzal Aghaei 40 47 0 11 Jun 2024
Nonlinearity Enhanced Adaptive Activation Functions David Yevick 25 1 0 29 Mar 2024
Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning Farhad Pourkamali-Anaraki Jamal F. Husseini Scott E. Stapleton UD 48 2 0 21 Feb 2024
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics Michael Penwarden H. Owhadi Robert M. Kirby AI4CE 22 1 0 16 Feb 2024
Adaptive Activation Functions for Predictive Modeling with Sparse Experimental Data Farhad Pourkamali-Anaraki Tahamina Nasrin Robert E. Jensen Amy M. Peterson Christopher J. Hansen 24 7 0 08 Feb 2024
RiemannONets: Interpretable Neural Operators for Riemann Problems Ahmad Peyvan Vivek Oommen Ameya Dilip Jagtap George Karniadakis AI4CE 38 22 0 16 Jan 2024
Data-driven localized waves and parameter discovery in the massive Thirring model via extended physics-informed neural networks with interface zones Christian Berger Sadok Ben Toumia Zijian Zhou Zhenya Yan PINN 28 8 0 29 Sep 2023
Deep smoothness WENO scheme for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators Tatiana Kossaczká Ameya Dilip Jagtap Matthias Ehrhardt 15 1 0 18 Sep 2023
Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines Kamaljyoti Nath Xuhui Meng Daniel J. Smith George Karniadakis PINN 20 20 0 26 Apr 2023
iPINNs: Incremental learning for Physics-informed neural networks Aleksandr Dekhovich M. Sluiter David Tax Miguel A. Bessa AI4CE DiffM 20 10 0 10 Apr 2023
Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN Shahed Rezaei Ahmad Moeineddin Ali Harandi PINN 32 18 0 10 Apr 2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions Michael Penwarden Ameya Dilip Jagtap Shandian Zhe George Karniadakis Robert M. Kirby PINN AI4CE 23 57 0 28 Feb 2023
Learning stiff chemical kinetics using extended deep neural operators S. Goswami Ameya Dilip Jagtap H. Babaee Bryan T. Susi George Karniadakis AI4CE 35 37 0 23 Feb 2023
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains Ali Harandi Ahmad Moeineddin Michael Kaliske Stefanie Reese Shahed Rezaei AI4CE PINN 25 42 0 09 Feb 2023
Self-Supervised Learning for Data Scarcity in a Fatigue Damage Prognostic Problem A. Akrim C. Gogu R. Vingerhoeds M. Salaün AI4CE 32 23 0 20 Jan 2023
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media Salah A. Faroughi Ramin Soltanmohammad Pingki Datta S. K. Mahjour S. Faroughi 18 22 0 17 Dec 2022
Modular machine learning-based elastoplasticity: generalization in the context of limited data J. Fuhg Craig M. Hamel K. Johnson Reese E. Jones N. Bouklas 29 48 0 15 Oct 2022
A Lightweight and Gradient-Stable Neural Layer Yueyao Yu Yin Zhang 26 0 0 08 Jun 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
Review and Comparison of Commonly Used Activation Functions for Deep Neural Networks Tomasz Szandała 59 274 0 15 Oct 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 331 1,049 0 10 Feb 2017