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# Topic Models Edit

74 papers with code · Miscellaneous

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# A Coefficient of Determination for Probabilistic Topic Models

20 Nov 2019TommyJones/tidylda

This research proposes a new (old) metric for evaluating goodness of fit in topic models, the coefficient of determination, or $R^2$.

1
20 Nov 2019

# Statistical Model Aggregation via Parameter Matching

We consider the problem of aggregating models learned from sequestered, possibly heterogeneous datasets.

2
01 Nov 2019

# Prediction Focused Topic Models via Vocab Selection

12 Oct 2019jasonren12/PredictionFocusedTopicModel

Supervised topic models are often sought to balance prediction quality and interpretability.

0
12 Oct 2019

# Learning document embeddings along with their uncertainties

20 Aug 2019skesiraju/BaySMM

We present Bayesian subspace multinomial model (Bayesian SMM), a generative log-linear model that learns to represent documents in the form of Gaussian distributions, thereby encoding the uncertainty in its co-variance.

8
20 Aug 2019

# The Dynamic Embedded Topic Model

Topic modeling analyzes documents to learn meaningful patterns of words.

23
12 Jul 2019

# Topic Modeling in Embedding Spaces

To this end, we develop the Embedded Topic Model (ETM), a generative model of documents that marries traditional topic models with word embeddings.

137
08 Jul 2019

# Scalable Collapsed Inference for High-Dimensional Topic Models

In this paper, we develop an online inference algorithm for topic models which leverages stochasticity to scale well in the number of documents, sparsity to scale well in the number of topics, and which operates in the collapsed representation of the topic model for improved accuracy and run-time performance.

0
01 Jun 2019

# Tracing Forum Posts to MOOC Content using Topic Analysis

15 Apr 2019awwong1/topic-traceability

Massive Open Online Courses are educational programs that are open and accessible to a large number of people through the internet.

1
15 Apr 2019

# Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns

11 Mar 2019atcemgil/bam

We introduce a dynamic generative model, Bayesian allocation model (BAM), which establishes explicit connections between nonnegative tensor factorization (NTF), graphical models of discrete probability distributions and their Bayesian extensions, and the topic models such as the latent Dirichlet allocation.

1
11 Mar 2019

# Vector space explorations of literary language

Previous research showed that ratings of literariness are predictable from texts to a substantial extent using machine learning, suggesting that it may be possible to explain the consensus among readers on which novels are literary as a consensus on the kind of writing style that characterizes literature.

3
09 Feb 2019