research
∙
09/20/2023
Spiking NeRF: Making Bio-inspired Neural Networks See through the Real World
Spiking neuron networks (SNNs) have been thriving on numerous tasks to l...
share
research
∙
03/02/2023
Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication
Training Graph Neural Networks (GNNs) on large graphs is challenging due...
research
∙
02/01/2023
A^2Q: Aggregation-Aware Quantization for Graph Neural Networks
As graph data size increases, the vast latency and memory consumption du...
research
∙
11/25/2022
DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection
Fully convolutional detectors discard the one-to-many assignment and ado...
research
∙
10/22/2022
Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets
Vision Transformers has demonstrated competitive performance on computer...
research
∙
08/03/2022
PalQuant: Accelerating High-precision Networks on Low-precision Accelerators
Recently low-precision deep learning accelerators (DLAs) have become pop...
research
∙
05/24/2022
Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision
Deep learning (DL) shows its prosperity in a wide variety of fields. The...
research
∙
04/06/2022
MixFormer: Mixing Features across Windows and Dimensions
While local-window self-attention performs notably in vision tasks, it s...
research
∙
04/04/2022
Soft Threshold Ternary Networks
Large neural networks are difficult to deploy on mobile devices because ...
research
∙
09/03/2021
Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters
Modern GPU datacenters are critical for delivering Deep Learning (DL) mo...
research
∙
09/01/2021
Architecture Aware Latency Constrained Sparse Neural Networks
Acceleration of deep neural networks to meet a specific latency constrai...
research
∙
04/07/2021
HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap
Recently, heatmap regression models have become the mainstream in locati...
research
∙
01/21/2021
Generative Zero-shot Network Quantization
Convolutional neural networks are able to learn realistic image priors f...
research
∙
09/24/2019
A System-Level Solution for Low-Power Object Detection
Object detection has made impressive progress in recent years with the h...
research
∙
07/23/2019
Compact Global Descriptor for Neural Networks
Long-range dependencies modeling, widely used in capturing spatiotempora...
research
∙
02/08/2018
From Hashing to CNNs: Training BinaryWeight Networks via Hashing
Deep convolutional neural networks (CNNs) have shown appealing performan...
research
∙
02/03/2018
Recent Advances in Efficient Computation of Deep Convolutional Neural Networks
Deep neural networks have evolved remarkably over the past few years and...
research
∙
02/03/2018
A Survey on Acceleration of Deep Convolutional Neural Networks
Deep Neural Networks have achieved remarkable progress during the past f...
research
∙
12/21/2015
