Search Results for author:
Found 8 papers, 3 papers with code
PGformer: Proxy-Bridged Game Transformer for Multi-Person Highly Interactive Extreme Motion Prediction
Multi-person motion prediction is a challenging task, especially for real-world scenarios of highly interacted persons.
Cross-Layer Retrospective Retrieving via Layer Attention
Motivated by this, we devise a cross-layer attention mechanism, called multi-head recurrent layer attention (MRLA), that sends a query representation of the current layer to all previous layers to retrieve query-related information from different levels of receptive fields.
High-Frequency-Based Volatility Model with Network Structure
This paper introduces one new multivariate volatility model that can accommodate an appropriately defined network structure based on low-frequency and high-frequency data.
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks
While recently many designs have been proposed to improve the model efficiency of convolutional neural networks (CNNs) on a fixed resource budget, theoretical understanding of these designs is still conspicuously lacking.
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation
This paper introduces a concept of layer aggregation to describe how information from previous layers can be reused to better extract features at the current layer.
Rethinking Compressed Convolution Neural Network from a Statistical Perspective
Many designs have recently been proposed to improve the model efficiency of convolutional neural networks (CNNs) at a fixed resource budget, while there is a lack of theoretical analysis to justify them.
Do RNN and LSTM have Long Memory?
The LSTM network was proposed to overcome the difficulty in learning long-term dependence, and has made significant advancements in applications.
Compact Autoregressive Network
Autoregressive networks can achieve promising performance in many sequence modeling tasks with short-range dependence.
