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Found 16 papers, 1 papers with code
Root Cause Explanation of Outliers under Noisy Mechanisms
We then represent the functional form of a target outlier leaf as a function of the node and edge noises.
Robust Estimation of Causal Heteroscedastic Noise Models
One solution to this problem is assuming that cause and effect are generated from a structural causal model, enabling identification of the causal direction after estimating the model in each direction.
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Score-based approaches in the structure learning task are thriving because of their scalability.
Memory-Augmented Theory of Mind Network
Social reasoning necessitates the capacity of theory of mind (ToM), the ability to contextualise and attribute mental states to others without having access to their internal cognitive structure.
Fast Conditional Network Compression Using Bayesian HyperNetworks
We introduce a conditional compression problem and propose a fast framework for tackling it.
Learning Theory of Mind via Dynamic Traits Attribution
Inspired by the observation that humans often infer the character traits of others, then use it to explain behaviour, we propose a new neural ToM architecture that learns to generate a latent trait vector of an actor from the past trajectories.
Learning to Transfer Role Assignment Across Team Sizes
In particular, we train a role assignment network for small teams by demonstration and transfer the network to larger teams, which continue to learn through interaction with the environment.
Unsupervised Anomaly Detection on Temporal Multiway Data
These include the capacity of the compact matrix LSTM to compress noisy data near perfectly, making the strategy of compressing-decompressing data ill-suited for anomaly detection under the noise.
Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning
In psychological game theory, guilt aversion necessitates modelling of agents that have theory about what other agents think, also known as Theory of Mind (ToM).
Variational Hyper-Encoding Networks
Given a target distribution, we predict the posterior distribution of the latent code, then use a matrix-network decoder to generate a posterior distribution q(\theta).
Measuring English Readability for Vietnamese Speakers
This study introduces a first approximation to readability of English text for VL1, with suggestions for further improvements.
Resset: A Recurrent Model for Sequence of Sets with Applications to Electronic Medical Records
The same hold for the bag of treatments.
Intelligent Device Discovery in the Internet of Things - Enabling the Robot Society
The Internet of Things (IoT) is continuously growing to connect billions of smart devices anywhere and anytime in an Internet-like structure, which enables a variety of applications, services and interactions between human and objects.
Finding Algebraic Structure of Care in Time: A Deep Learning Approach
The interaction between diseases and treatments at a visit is modeled as the residual of the diseases minus the treatments.
Deep Learning to Attend to Risk in ICU
At the reasoning layer, evidences across time steps are weighted and combined.
Deepr: A Convolutional Net for Medical Records
On top of the sequence is a convolutional neural net that detects and combines predictive local clinical motifs to stratify the risk.
