Sociology
29 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Sociology
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
BIG-bench
Most implemented papers
A Simple Algorithm for Scalable Monte Carlo Inference
The methods of statistical physics are widely used for modelling complex networks.
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data
octeufer/Adversarial-Balancing-based-representation-learning-for-Causal-Effect-Inference
•
•
The challenges for this problem are two-fold: on the one hand, we have to derive a causal estimator to estimate the causal quantity from observational data, where there exists confounding bias; on the other hand, we have to deal with the identification of CATE when the distribution of covariates in treatment and control groups are imbalanced.
Practical and scalable simulations of non-Markovian stochastic processes
While analytic solutions often cannot be derived, existing simulation frameworks can generate stochastic trajectories compatible with the dynamical laws underlying the random phenomena.
A Spectral Framework for Tracking Communities in Evolving Networks
Discovering and tracking communities in time-varying networks is an important task in network science, motivated by applications in fields ranging from neuroscience to sociology.
Community detection in graphs
The modern science of networks has brought significant advances to our understanding of complex systems.
Semantics derived automatically from language corpora contain human-like biases
Here we show for the first time that human-like semantic biases result from the application of standard machine learning to ordinary language---the same sort of language humans are exposed to every day.
A network approach to topic models
By adapting existing community-detection methods -- using a stochastic block model (SBM) with non-parametric priors -- we obtain a more versatile and principled framework for topic modeling (e. g., it automatically detects the number of topics and hierarchically clusters both the words and documents).
Latent Variable Time-varying Network Inference
The estimation of the contribution of the latent factors is embedded in the model which produces both sparse and low-rank components for each time point.
A Recurrent Graph Neural Network for Multi-Relational Data
bioannidis/adaptive_recurrent_graph_neural_network
•
•
The era of data deluge has sparked the interest in graph-based learning methods in a number of disciplines such as sociology, biology, neuroscience, or engineering.
