research
∙
03/07/2023
Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Pretraining a neural network on a large dataset is becoming a cornerston...
share
research
∙
09/29/2022
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
In the last years, neural networks (NN) have evolved from laboratory env...
research
∙
09/29/2022
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Learning representations of neural network weights given a model zoo is ...
research
∙
07/22/2022
Hyper-Representations for Pre-Training and Transfer Learning
Learning representations of neural network weights given a model zoo is ...
research
∙
07/20/2022
Pretraining a Neural Network before Knowing Its Architecture
Training large neural networks is possible by training a smaller hyperne...
research
∙
01/24/2022
On Evaluation Metrics for Graph Generative Models
In image generation, generative models can be evaluated naturally by vis...
research
∙
10/29/2021
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Discovering a solution in a combinatorial space is prevalent in many rea...
research
∙
10/25/2021
Parameter Prediction for Unseen Deep Architectures
Deep learning has been successful in automating the design of features i...
research
∙
07/11/2020
Generative Graph Perturbations for Scene Graph Prediction
Inferring objects and their relationships from an image is useful in man...
research
∙
05/17/2020
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
Scene graph generation (SGG) aims to predict graph-structured descriptio...
research
∙
09/23/2019
Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions
Graphs evolving over time are a natural way to represent data in many do...
research
∙
07/21/2019
Image Classification with Hierarchical Multigraph Networks
Graph Convolutional Networks (GCNs) are a class of general models that c...
research
∙
05/08/2019
Understanding attention in graph neural networks
We aim to better understand attention over nodes in graph neural network...
research
∙
11/23/2018
Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules
Spectral Graph Convolutional Networks (GCNs) are a generalization of con...
research
∙
11/13/2017
Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video
In this paper we describe a solution to our entry for the emotion recogn...
research
∙
06/02/2016