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Found 7 papers, 2 papers with code
A Neural Network Subgrid Model of the Early Stages of Planet Formation
Planet formation is a multi-scale process in which the coagulation of $\mathrm{\mu m}$-sized dust grains in protoplanetary disks is strongly influenced by the hydrodynamic processes on scales of astronomical units ($\approx 1. 5\times 10^8 \,\mathrm{km}$).
Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision
In this article we propose a hybrid architecture for end-to-end training of deep neural networks for event-based pattern recognition and object detection, combining a spiking neural network (SNN) backbone for efficient event-based feature extraction, and a subsequent analog neural network (ANN) head to solve synchronous classification and detection tasks.
SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning
We validate SOSP-H by comparing it to our second method SOSP-I that uses a well-established Hessian approximation, and to numerous state-of-the-art methods.
ItNet: iterative neural networks with small graphs for accurate, efficient and anytime semantic segmentation
However, to exploit these benefits the computational graph of a neural network has to fit into the in-computation memory of these hardware systems that is usually rather limited in size.
On the cost of homogeneous network building blocks and parameter sharing
We compensate for both the homogeneity of the network architecture and the weight sharing by increasing the number of multiply-accumulate operations by a factor of 3, respectively.
The streaming rollout of deep networks - towards fully model-parallel execution
Deep neural networks, and in particular recurrent networks, are promising candidates to control autonomous agents that interact in real-time with the physical world.
Pattern representation and recognition with accelerated analog neuromorphic systems
Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks.
