A Theory of Generative ConvNet
ICML'16, 2016. [All Versions]. The authors show that a generative random field model, which they call generative ConvNet, can be derived from the commonly used discriminative ConvNet, by assuming a ConvNet for multi-category classification and assuming one of the category is a…
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Cooperative Training of Descriptor and Generator Networks ieeexplore.ieee.org
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. [All Versions]. This paper studies the cooperative training of two generative models for image modeling and synthesis. Both models are parametrized by convolutional neural networks (ConvNets). The first model…
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Unsupervised Representaton Learning with Deep Convolutional Generative Adversarial Networks arxiv.org
ICLR'16, 2016. [All Versions].
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Generative Modeling Explained github.com
Statistical Machine Learning Tutorials, 2022. This tutorial on generative modeling is in part of Statistical Machine Learning Tutorial by Ying Nian Wu at UCLA Statistics. The tutorial goes over the key equations and algorithms for learning recent generative models, including…
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On the Complexity of Bayesian Generalization proceedings.mlr.press
ICML'23, 2023. [All Versions]. [Project]. [Models]. This work examines concept generalization at a large scale in the natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily studied isolated, focusing on confined and…
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Learning Task-General Representations with Generative Neuro-Symbolic Modeling arxiv.org
ICLR'21, 2021. [All Versions].
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Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same… proceedings.neurips.cc
NeurIPS'18, 2018. [All Versions]. Maching the learned pattern of neurons in different neural networks.
AGI & CoCoSci › Papers > Bayesian Modeling > Generative Model: “ICML'16, 2016. [All Versions]. The authors show that a generative random field model, which they call generative ConvNet, can be derived from the commonly used discriminative ConvNet, by assuming a ConvNet for multi-category classification and assuming one of the category is a…”