Pages that link to "Item:Q1892212"

The following pages link to On the computational power of neural nets (Q1892212):

Displaying 50 items.

• Analog quantum computing (AQC) and the need for time-symmetric physics (Q291575) (← links)
• Computation with perturbed dynamical systems (Q355515) (← links)
• The ARNN model relativises \(\mathrm{P}=\mathrm{NP}\) and \(\mathrm{P}\neq \mathrm{NP}\) (Q391177) (← links)
• Noise-robust realization of Turing-complete cellular automata by using neural networks with pattern representation (Q418663) (← links)
• The expressive power of analog recurrent neural networks on infinite input streams (Q428898) (← links)
• On probabilistic analog automata (Q596111) (← links)
• On the computation of Boolean functions by analog circuits of bounded fan-in (Q676434) (← links)
• Transiently chaotic neural networks with piecewise linear output functions (Q711939) (← links)
• Expressive power of first-order recurrent neural networks determined by their attractor dynamics (Q736603) (← links)
• Complexity of reachability problems for finite discrete dynamical systems (Q856411) (← links)
• Analog computation through high-dimensional physical chaotic neuro-dynamics (Q933433) (← links)
• The nature of the extended analog computer (Q933439) (← links)
• Vapnik-Chervonenkis dimension of recurrent neural networks (Q1265745) (← links)
• Computability with low-dimensional dynamical systems (Q1334658) (← links)
• Symmetric discrete universal neural networks (Q1349870) (← links)
• A family of universal recurrent networks (Q1349875) (← links)
• A McCulloch-Pitts neural net to characterize even linear languages (Q1350293) (← links)
• Complete controllability of continuous-time recurrent neural networks (Q1391523) (← links)
• Stochastic analog networks and computational complexity (Q1578510) (← links)
• Analog computation with dynamical systems (Q1586961) (← links)
• Simulation of Turing machine with uEAC-computable functions (Q1665037) (← links)
• A brief review of neural networks based learning and control and their applications for robots (Q1687400) (← links)
• Quasi-periodic \(\beta\)-expansions and cut languages (Q1704578) (← links)
• Computational capabilities of analog and evolving neural networks over infinite input streams (Q1713481) (← links)
• Informational properties of neural nets performing algorithmic and logical tasks (Q1916524) (← links)
• Automata complete computation with Hodgkin-Huxley neural networks composed of synfire rings (Q1980415) (← links)
• Analog neuron hierarchy (Q1982432) (← links)
• Spiking neural P systems with target indications (Q1998881) (← links)
• Spiking neural P systems with structural plasticity and anti-spikes (Q2007721) (← links)
• Synthesizing context-free grammars from recurrent neural networks (Q2044212) (← links)
• Hamilton's rule, the evolution of behavior rules and the wizardry of control theory (Q2095402) (← links)
• A characterization of polynomial time computable functions from the integers to the reals using discrete ordinary differential equations (Q2104133) (← links)
• A statistical model of neural network learning via the Cramer-Rao lower bound (Q2132021) (← links)
• Metric entropy limits on recurrent neural network learning of linear dynamical systems (Q2134114) (← links)
• Spiking neural P systems with a flat maximally parallel use of rules (Q2152302) (← links)
• Subrecursive neural networks (Q2183681) (← links)
• A review on deep reinforcement learning for fluid mechanics (Q2245392) (← links)
• Where do Bayesian priors come from? (Q2460148) (← links)
• Computability with polynomial differential equations (Q2482915) (← links)
• The case for hypercomputation (Q2497872) (← links)
• How much can analog and hybrid systems be proved (super-)Turing (Q2497875) (← links)
• From Hopfield nets to recursive networks to graph machines: numerical machine learning for structured data (Q2575085) (← links)
• On the complexity of bounded time and precision reachability for piecewise affine systems (Q2636516) (← links)
• Pictorial reasoning with cell assemblies (Q2744899) (← links)
• Simple recurrent networks learn context-free and context-sensitive languages by counting. (Q2784810) (← links)
• Spiking neural P systems with astrocytes (Q2885114) (← links)
• The computational power of interactive recurrent neural networks (Q2919401) (← links)
• An analogue-digital Church-Turing thesis (Q2929623) (← links)
• Expressive Power of Non-deterministic Evolving Recurrent Neural Networks in Terms of Their Attractor Dynamics (Q2945562) (← links)
• Continuous-Time Symmetric Hopfield Nets Are Computationally Universal (Q3375307) (← links)