English
Related papers

Related papers: First Power Linear Unit with Sign

200 papers

In neural networks literature, there is a strong interest in identifying and defining activation functions which can improve neural network performance. In recent years there has been a renovated interest of the scientific community in…

Machine Learning · Computer Science 2021-03-01 Andrea Apicella , Francesco Donnarumma , Francesco Isgrò , Roberto Prevete

The goal of a recommendation system is to predict the interest of a user in a given item by exploiting the existing set of ratings as well as certain user/item features. A standard approach to modeling this problem is Inductive Matrix…

Machine Learning · Computer Science 2018-05-29 Kai Zhong , Zhao Song , Prateek Jain , Inderjit S. Dhillon

Signal temporal logic (STL) provides a user-friendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which guarantee…

Systems and Control · Computer Science 2019-03-12 Peter Varnai , Dimos V. Dimarogonas

The fractional polylogarithms, depending on a complex parameter $\a$, are defined by a series which is analytic inside the unit disk. After an elementary conversion of the series into an integral presentation, we show that the fractional…

Classical Analysis and ODEs · Mathematics 2009-07-16 Ovidiu Costin , Stavros Garoufalidis

Probabilistic power flow (PPF) is essential for quantifying operational uncertainty in modern distribution systems with high penetration of renewable generation and flexible loads. Conventional PPF methods primarily rely on Monte Carlo (MC)…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Weijie Xia , James Ciyu Qin , Edgar Mauricio Salazar Duque , Hongjin Du , Peter Palensky , Giovanni Sansavini , Pedro P. Vergara

In recent years, deep neural networks (DNNs) achieved unprecedented performance in many low-level vision tasks. However, state-of-the-art results are typically achieved by very deep networks, which can reach tens of layers with tens of…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Idan Kligvasser , Tamar Rott Shaham , Tomer Michaeli

A two-level system (2LS) is the most fundamental building block of matter. Its response to classical light is well known, as it converts pulses of coherent light into antibunched emission. However, recent theoretical proposals have…

Quantum Physics · Physics 2025-10-17 Juan Camilo López Carreño

Photonic neural networks have demonstrated their potential over the past decades, but have not yet reached the full extent of their capabilities. One reason for this lies in an essential component - the nonlinear activation function, which…

Optics · Physics 2025-02-26 Grigorii Slinkov , Steven Becker , Dirk Englund , Birgit Stiller

In the paper, the authors establish Maclaurin's series expansions and series identities for positive integer powers of the inverse sine function, for positive integer powers of the inverse hyperbolic sine function, for the composite of…

Combinatorics · Mathematics 2022-04-28 Bai-Ni Guo , Dongkyu Lim , Feng Qi

The threads of photonics are eagerly awaited to redefine the future of neuromorphic data processing, especially as the computing-intensive artificial intelligence models become an unavoidable part of our everyday lives. Still, there is much…

This paper proposes a novel multifunctional sensing platform based on multimode planar photonic crystals (PPCs). We analytically and numerically demonstrate that the reflection spectrum of PPCs exhibits multiple high-Q resonant modes, and…

Optics · Physics 2017-01-13 Yongyao Chen , Haijun Liu , Zhijian Zhang , Miao Yu

A wide variety of activation functions have been proposed for neural networks. The Rectified Linear Unit (ReLU) is especially popular today. There are many practical reasons that motivate the use of the ReLU. This paper provides new…

Machine Learning · Statistics 2020-10-19 Rahul Parhi , Robert D. Nowak

Current research suggests that the key factors in designing neural network architectures involve choosing number of filters for every convolution layer, number of hidden neurons for every fully connected layer, dropout and pruning. The…

Machine Learning · Computer Science 2020-09-17 Himanshu Pradeep Aswani , Amit Sethi

Activation functions are essential to introduce nonlinearity into neural networks, with the Rectified Linear Unit (ReLU) often favored for its simplicity and effectiveness. Motivated by the structural similarity between a shallow…

Machine Learning · Computer Science 2024-01-30 Jiayun Li , Yuxiao Cheng , Yiwen Lu , Zhuofan Xia , Yilin Mo , Gao Huang

Inductive logic programming is a form of machine learning based on mathematical logic that generates logic programs from given examples and background knowledge. In this project, we extend the Popper ILP system to make use of multi-task…

Machine Learning · Computer Science 2022-08-25 Bogdan Cretu , Andrew Cropper

The Gamma Factory (GF) initiative aims at the construction of a unique experimental tool exploiting resonant interaction of light with ultra-relativistic partially stripped ions (PSI) stored in circular accelerators at CERN. Resonant…

Atomic Physics · Physics 2022-05-31 J. Bieroń , M. W. Krasny , W. Płaczek , S. Pustelny

This paper proposes a learnable nonlinear activation mechanism specifically for convolutional neural network (CNN) termed as LENI, which learns to enhance the negative information in CNNs. In sharp contrast to ReLU which cuts off the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Zhicheng Cai , Chenglei Peng , Qiu Shen

Physical Unclonable Functions (PUFs) leverage manufacturing process imperfections that cause propagation delay discrepancies for the signals traveling along these paths. While PUFs can be used for device authentication and chip-specific key…

Cryptography and Security · Computer Science 2024-02-14 Michael Dominguez , Amin Rezaei

The proposed International Linear Collider (ILC) is well-suited for discovering physics beyond the Standard Model and for precisely unravelling the structure of the underlying physics. The physics return of the ILC can be maximized by the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Gudrid Moortgat-Pick

Planar commutative n-complex numbers of the form u=x_0+h_1x_1+h_2x_2+...+h_{n-1}x_{n-1} are introduced in an even number n of dimensions, the variables x_0,...,x_{n-1} being real numbers. The planar n-complex numbers can be described by the…

Complex Variables · Mathematics 2007-05-23 Silviu Olariu