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06/18/2020
A Representational Model of Grid Cells Based on Matrix Lie Algebras
The grid cells in the mammalian medial entorhinal cortex exhibit strikin...
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06/15/2020
Learning Latent Space Energy-Based Prior Model
The generator model assumes that the observed example is generated by a ...
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06/12/2020
Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC
Learning energy-based model (EBM) requires MCMC sampling of the learned ...
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06/11/2020
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
The goal of neural-symbolic computation is to integrate the connectionis...
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06/10/2020
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
This paper proposes a joint training method to learn both the variationa...
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04/20/2020
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense
Recent progress in deep learning is essentially based on a "big data for...
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04/02/2020
Generative PointNet: Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification
We propose a generative model of unordered point sets, such as point clo...
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12/04/2019
Learning Deep Generative Models with Short Run Inference Dynamics
This paper studies the fundamental problem of learning deep generative m...
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12/02/2019
Flow Contrastive Estimation of Energy-Based Models
This paper studies a training method to jointly estimate an energy-based...
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11/26/2019
Representation Learning: A Statistical Perspective
Learning representations of data is an important problem in statistics a...
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11/26/2019
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns
Dynamic patterns are characterized by complex spatial and motion pattern...
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11/19/2019
Deep Unsupervised Clustering with Clustered Generator Model
This paper addresses the problem of unsupervised clustering which remain...
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09/26/2019
Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns
Video sequences contain rich dynamic patterns, such as dynamic texture p...
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09/10/2019
Towards Interpretable Image Synthesis by Learning Sparsely Connected AND-OR Networks
This paper proposes interpretable image synthesis by learning hierarchic...
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09/01/2019
Neural Architecture Search for Joint Optimization of Predictive Power and Biological Knowledge
We report a neural architecture search framework, BioNAS, that is tailor...
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04/22/2019
On Learning Non-Convergent Short-Run MCMC Toward Energy-Based Model
This paper studies a curious phenomenon in learning energy-based model (...
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04/10/2019
Learning Trajectory Prediction with Continuous Inverse Optimal Control via Langevin Sampling of Energy-Based Models
Autonomous driving is a challenging multiagent domain which requires opt...
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04/09/2019
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction
Accurate prediction of others' trajectories is essential for autonomous ...
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03/29/2019
On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models
This study investigates the effects Markov Chain Monte Carlo (MCMC) samp...
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02/07/2019
Multimodal Conditional Learning with Fast Thinking Policy-like Model and Slow Thinking Planner-like Model
This paper studies the supervised learning of the conditional distributi...
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01/24/2019
Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1
This paper entertains the hypothesis that the primary purpose of the cel...
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01/21/2019
Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract)
This paper presents an unsupervised method to learn a neural network, na...
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01/21/2019
Network Transplanting (extended abstract)
This paper focuses on a new task, i.e., transplanting a category-and-tas...
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01/20/2019
Inducing Sparse Coding and And-Or Grammar from Generator Network
We introduce an explainable generative model by applying sparse operatio...
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01/08/2019
Interpretable CNNs
This paper proposes a generic method to learn interpretable convolutiona...
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12/28/2018
Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model
This paper proposes the divergence triangle as a framework for joint tra...
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12/27/2018
Learning Dynamic Generator Model by Alternating Back-Propagation Through Time
This paper studies the dynamic generator model for spatial-temporal proc...
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12/18/2018
Explanatory Graphs for CNNs
This paper introduces a graphical model, namely an explanatory graph, wh...
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12/18/2018
Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering
In this paper, we present a method to mine object-part patterns from con...
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10/31/2018
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation
Holistic 3D indoor scene understanding refers to jointly recovering the ...
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10/12/2018
Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion
This paper proposes a model for learning grid-like units for spatial awa...
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10/09/2018
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
The pattern theory of Grenander is a mathematical framework where the pa...
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10/01/2018
Interactive Agent Modeling by Learning to Probe
The ability of modeling the other agents, such as understanding their in...
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06/16/2018
Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry
We propose a deformable generator model to disentangle the appearance an...
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05/18/2018
Unsupervised Learning of Neural Networks to Explain Neural Networks
This paper presents an unsupervised method to learn a neural network, na...
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05/14/2018
Replicating Active Appearance Model by Generator Network
A recent Cell paper [Chang and Tsao, 2017] reports an interesting discov...
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04/26/2018
Network Transplanting
This paper focuses on a novel problem, i.e., transplanting a category-an...
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04/02/2018
Learning Descriptor Networks for 3D Shape Synthesis and Analysis
This paper proposes a 3D shape descriptor network, which is a deep convo...
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02/01/2018
Interpreting CNNs via Decision Trees
This paper presents a method to learn a decision tree to quantitatively ...
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10/02/2017
Interpretable Convolutional Neural Networks
This paper proposes a method to modify traditional convolutional neural ...
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09/26/2017
Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence
This paper proposes a minimal contrastive divergence method for learning...
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08/13/2017
A Cost-Sensitive Visual Question-Answer Framework for Mining a Deep And-OR Object Semantics from Web Images
This paper presents a cost-sensitive Question-Answering (QA) framework f...
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08/05/2017
Interpreting CNN Knowledge via an Explanatory Graph
This paper learns a graphical model, namely an explanatory graph, which ...
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08/05/2017
Interactively Transferring CNN Patterns for Part Localization
In the scenario of one/multi-shot learning, conventional end-to-end lear...
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04/11/2017
Mining Object Parts from CNNs via Active Question-Answering
Given a convolutional neural network (CNN) that is pre-trained for objec...
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11/14/2016
Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning
This paper proposes a learning strategy that extracts object-part concep...
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09/29/2016
Cooperative Training of Descriptor and Generator Networks
This paper studies the cooperative training of two probabilistic models ...
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07/01/2016
Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Spar
Brain networks in fMRI are typically identified using spatial independen...
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06/28/2016
Alternating Back-Propagation for Generator Network
This paper proposes an alternating back-propagation algorithm for learni...
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06/03/2016