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Latest papers without code

OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation

2 May 2021

Specifically, we expect to approximate the real joint distribution over the partial observation and latent variables, thus infer the unseen targets respectively.

LATENT VARIABLE MODELS

Learning Latent and Hierarchical Structures in Cognitive Diagnosis Models

5 Apr 2021

Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models that are widely used in modern educational, psychological, social and biological sciences.

LATENT VARIABLE MODELS

High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees

1 Apr 2021

In this paper, we develop a general framework to design differentially private expectation-maximization (EM) algorithms in high-dimensional latent variable models, based on the noisy iterative hard-thresholding.

LATENT VARIABLE MODELS

Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication

1 Apr 2021

Neural networks and other machine learning models compute continuous representations, while humans communicate with discrete symbols.

LATENT VARIABLE MODELS

Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction

6 Mar 2021

Our key insight is that greedy and modular optimization of hierarchical autoencoders can simultaneously address both the memory constraints and the optimization challenges of large-scale video prediction.

LATENT VARIABLE MODELS VIDEO PREDICTION

Deep Stochastic Volatility Model

25 Feb 2021

We propose a deep stochastic volatility model (DSVM) based on the framework of deep latent variable models.

LATENT VARIABLE MODELS VARIATIONAL INFERENCE

Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding

22 Feb 2021

Naively applied, our schemes would require more initial bits than the standard bits-back coder, but we show how to drastically reduce this additional cost with couplings in the latent space.

LATENT VARIABLE MODELS

Causal Mediation Analysis with Hidden Confounders

21 Feb 2021

An important problem in causal inference is to break down the total effect of treatment into different causal pathways and quantify the causal effect in each pathway.

CAUSAL INFERENCE LATENT VARIABLE MODELS

A Critical Look At The Identifiability of Causal Effects with Deep Latent Variable Models

12 Feb 2021

Using deep latent variable models in causal inference has attracted considerable interest recently, but an essential open question is their identifiability.

CAUSAL INFERENCE LATENT VARIABLE MODELS

Do-calculus enables causal reasoning with latent variable models

12 Feb 2021

Despite this intuitive causal interpretation, a directed acyclic latent variable model trained on data is generally insufficient for causal reasoning, as the required model parameters may not be uniquely identified.

LATENT VARIABLE MODELS