Artificial Neural Networks (ANN) are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They have been used in diverse applications and have shown to be particularly effective in system identification and modeling as they are fault tolerant and ...
We have developed a graphically oriented, general purpose simulation system to facilitate the modeling of neural networks. The simulator is implemented under UNIX and X-windows and is designed to support simulations at many levels of det... MA Wilson,MA Wilson,US Bhalla,... - Advances in Neur...
energy range on the GDB-10to13 CCSD(T)*/CBS benchmark. Recall that each ANI model is an ensemble average over eight neural networks. Without an ensemble of networks, the MAD and RMSD of ANI models degrades by about 25%25. Supplementary Table5provides errors for all methods within the ...
2.A special-purpose hardware chip for training neural networks, the special-purpose hardware chip comprising:a scalar processor configured to control computational operation of the special-purpose hardware chip;a vector processor having a 2-dimensional array of vector processing units; anda matrix multip...
On-chip and inter-chip networks for modeling large-scale neural systems power-efficiency, and fault-tolerance, and is intended to yield a general-purpose platform for the real-time simulation of large-scale spiking neural syste... S Furber,S Temple,A Brown - IEEE International Symposium on Cir...
Publication|Publication The inner workings of neural networks can be better understood if we can fully decipher the information encoded in neural activations. In this paper, we argue that this information is embodied by the subset of inputs that give rise to similar...
A general purpose neuro-adaptive controller, which realizes an indirect-adaptive control strategy, is introduced. The proposed algorithm is based on the use of two Multi-Layer feed-forward Perceptron (MLP) Neural Networks (NNs), which are trained using a momentum back-propagation (MBP) algorithm....
R. et al. ChampKit: a framework for rapid evaluation of deep neural networks for patch-based histopathology classification. Computer Methods and Programs in Biomedicine 239, 107631 (2023). Article PubMed PubMed Central Google Scholar Zhang, J. et al. Gigapixel whole-slide images classification ...
Python library for extracting mini-batches of data from a data source for the purpose of training neural networks - Britefury/batchup
Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010). Article ADS PubMed Google Scholar Batzner, S. et al. E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. Nat. Commun. ...