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Found 6 papers, 1 papers with code
ACC-ViT : Atrous Convolution's Comeback in Vision Transformers
At present two classes of attentions prevail in vision transformers, regional and sparse attention.
HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
The surge in prompt-based learning within Natural Language Processing (NLP) suggests the potential of adapting a "pre-train, prompt" paradigm to graphs as an alternative.
Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration
Given an environment (e. g., a simulator) for evaluating samples in a specified design space and a set of weighted evaluation metrics -- one can use Theta-Resonance, a single-step Markov Decision Process (MDP), to train an intelligent agent producing progressively more optimal samples.
Fully Convolutional Scene Graph Generation
This paper presents a fully convolutional scene graph generation (FCSGG) model that detects objects and relations simultaneously.
The Impact of Hole Geometry on Relative Robustness of In-Painting Networks: An Empirical Study
In this paper, we study the robustness of a given in-painting neural network against variations in hole geometry distributions.
A Convolutional Neural Network Approach for Half-Pel Interpolation in Video Coding
To further improve the coding efficiency, sub-pel motion compensation has been utilized, which requires interpolation of fractional samples.
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