Results 21 to 30 of about 751,622 (266)

Boosting Neural Networks [PDF]

Neural Computation, 2000
Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, Ada Boost, has been applied with great success to several benchmark machine learning problems using mainly decision trees as base classifiers.
Holger Schwenk, Yoshua Bengio
openaire   +2 more sources

Compactness of Neural Networks

Formalized Mathematics, 2022
Summary In this article, Feed-forward Neural Network is formalized in the Mizar system [1], [2]. First, the multilayer perceptron [6], [7], [8] is formalized using functional sequences. Next, we show that a set of functions generated by these neural networks satisfies equicontinuousness and equiboundedness property [10], [5]. At last,
Keiichi Miyajima, Hiroshi Yamazaki
openaire   +1 more source

Generating Neural Networks with Neural Networks

CoRR, 2018
Hypernetworks are neural networks that generate weights for another neural network. We formulate the hypernetwork training objective as a compromise between accuracy and diversity, where the diversity takes into account trivial symmetry transformations of the target network. We explain how this simple formulation generalizes variational inference.
openaire   +2 more sources

An exact mapping from ReLU networks to spiking neural networks

, 2023
Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge.
Wulfram Gerstner, Ana Stanojevic, Cherubini, Giovanni, Stanisław Woźniak, Bellec, Guillaume, Pantazi, Angeliki, Angeliki Pantazi, Giovanni Cherubini, Woźniak, Stanisław, Guillaume Bellec, Gerstner, Wulfram, Stanojevic, Ana   +11 more
core   +1 more source

Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning

, 2016
Biological brains exhibit a remarkable capacity to recognise real-world patterns effectively. Despite major advances in neuroscience over the last few decades, an understanding of the brain's underlying mechanisms for pattern recognition remains ...
Daniel E. Padilla, McDonnell, M.D., Mark D. McDonnell, Padilla, D.E.   +3 more
core   +1 more source

Prediction of Convergence Dynamics of Design Performance using Differential Recurrent Neural Networks [PDF]

, 2008
Computational Fluid Dynamics (CFD) simulations have been extensively used in many aerodynamic design optimization problems, such as wing and turbine blade shape design optimization.
Sendhoff, Bernhard, Yaochu Jin, Bernhard Sendhoff, Jin, Yaochu, Kowalczykiewicz, Michal, Yi Cao, Cao, Yi, Michal Kowalczykiewicz   +7 more
core   +1 more source

Increased Risk of Sarcomas in Children With Congenital Anomalies: Findings From the Genetic Overlap Between Anomalies and Cancer in Kids (GOBACK) Registry Linkage Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric sarcomas are a heterogeneous group of tumors that contribute disproportionately to cancer mortality in children. Although congenital anomalies are among the strongest known risk factors for childhood cancer, the risk of specific sarcoma subtypes among affected individuals has not yet been thoroughly evaluated. Procedure We
Russ Wolters, Ji Yun Tark, Tiffany M. Chambers, Tania A. Desrosiers, Michael E. Scheurer, Charles Shumate, Wendy N. Nembhard, Mahsa M. Yazdy, Eirini Nestoridi, Amanda E. Janitz, Jean Paul Tanner, Russell S. Kirby, Jason L. Salemi, Yao Yu, Chad D. Huff, Sharon E. Plon, Philip J. Lupo, Jeremy M. Schraw   +17 more
wiley   +1 more source

Reciprocal control of viral infection and phosphoinositide dynamics

FEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source

Neural Network Branching for Neural Network Verification

CoRR, 2019
Formal verification of neural networks is essential for their deployment in safety-critical areas. Many available formal verification methods have been shown to be instances of a unified Branch and Bound (BaB) formulation. We propose a novel framework for designing an effective branching strategy for BaB.
Jingyue Lu, M. Pawan Kumar
openaire   +3 more sources

Interacting neural networks [PDF]

Physical Review E, 2000
Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbour. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated.
Kinzel, W., Metzler, R., Kanter, I.
openaire   +3 more sources