Parameter Prediction
14 papers with code • 1 benchmarks • 2 datasets
DeepNets-1M
DrivAerNet
Most implemented papers
Diet Networks: Thin Parameters for Fat Genomics
It is based on the idea that we can first learn or provide a distributed representation for each input feature (e. g. for each position in the genome where variations are observed), and then learn (with another neural network called the parameter prediction network) how to map a feature's distributed representation to the vector of parameters specific to that feature in the classifier neural network (the weights which link the value of the feature to each of the hidden units).
Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks
Meta learning has attracted much attention recently in machine learning community.
WISE: Whitebox Image Stylization by Example-based Learning
Image-based artistic rendering can synthesize a variety of expressive styles using algorithmic image filtering.
Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction
HyeonwooNoh/DPPnet
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CVPR 2016
We tackle image question answering (ImageQA) problem by learning a convolutional neural network (CNN) with a dynamic parameter layer whose weights are determined adaptively based on questions.
Decision Trees for Decision-Making under the Predict-then-Optimize Framework
We consider the use of decision trees for decision-making problems under the predict-then-optimize framework.
Parameter Prediction for Unseen Deep Architectures
facebookresearch/ppuda
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NeurIPS 2021
We introduce a large-scale dataset of diverse computational graphs of neural architectures - DeepNets-1M - and use it to explore parameter prediction on CIFAR-10 and ImageNet.
Estimating relative diffusion from 3D micro-CT images using CNNs
In the past several years, convolutional neural networks (CNNs) have proven their capability to predict characteristic quantities in porous media research directly from pore-space geometries.
ParamNet: A Dynamic Parameter Network for Fast Multi-to-One Stain Normalization
khtao/paramnet
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Stain normalization can effectively reduce the differences in color and brightness of digital pathology images, thus improving the performance of computer-aided diagnostic systems.
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation
sbj028/deepconvolutionalforestparameterregression
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These results are consistent for experiments on above-ground biomass prediction in Tanzania and stem volume prediction in Norway, representing a diversity in parameters and forest types that emphasises the robustness of the approach.
Controlling Geometric Abstraction and Texture for Artistic Images
MartinBuessemeyer/Artistic-Texture-Control
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We present a novel method for the interactive control of geometric abstraction and texture in artistic images.
