Pinned Repositories
180651
air-traffic-control
16.35 Final Project Spring 2014
air-traffic-simulation
Next version because I messed up the last repo
biasCDA
Mitigating Gender Bias by Counterfactual Data Augmentation
causal-probe
csn
Code for Concept Subspace Networks (CSN)
fair-baselines
Implementations of different fair classification methods
FIRM-OMPL
C++ FIRM implementation using OMPL as a backend
human-guided-abstractions
Code for Human-Guided Complexity-Controlled Abstractions, including VQ-VIBC neural architecture.
vqvib_neurips2022
Codebase for VQ-VIB implementation and color experiments based on "Trading off Utility, Informativeness, and Complexity in Emergent Communication" NeurIPS 2022
mycal-tucker's Repositories
mycal-tucker/vqvib_neurips2022
Codebase for VQ-VIB implementation and color experiments based on "Trading off Utility, Informativeness, and Complexity in Emergent Communication" NeurIPS 2022
mycal-tucker/causal-probe
mycal-tucker/human-guided-abstractions
Code for Human-Guided Complexity-Controlled Abstractions, including VQ-VIBC neural architecture.
mycal-tucker/csn
Code for Concept Subspace Networks (CSN)
mycal-tucker/fair-baselines
Implementations of different fair classification methods
mycal-tucker/180651
mycal-tucker/biasCDA
Mitigating Gender Bias by Counterfactual Data Augmentation
mycal-tucker/stalker-drone
Repo for the code for 16.31 stalker drone project.
mycal-tucker/comp_psycholinguistics
Repo for course material for Computational Psycholinguistics
mycal-tucker/conll2017
mycal-tucker/ec-nl
inking Emergent and Natural Languages via Corpus Transfer
mycal-tucker/embo-github-mirror
A Python implementation of the Information Bottleneck analysis framework (Tishby, Pereira, Bialek 2000), especially geared towards the analysis of concrete, finite-size data sets. **GitHub mirror**: development happens at https://gitlab.com/epiasini/embo
mycal-tucker/emergent_communication_at_scale
mycal-tucker/gitignore
A collection of useful .gitignore templates
mycal-tucker/ib-color-naming
mycal-tucker/ib-explanations
mycal-tucker/ib_xai
Code for ''An Information Bottleneck Characterization of the Understanding-Workload Tradeoff in Human-Centered Explainable AI'' by Lindsay Sanneman*, Mycal Tucker*, and Julie Shah at FaCCT 2024
mycal-tucker/IC3Net
Code for ICLR 2019 paper: Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
mycal-tucker/intersections
TODO pithy descriptioin
mycal-tucker/keras
Deep Learning for humans
mycal-tucker/marl-ae-comm
PyTorch implementation for all models and environments in the paper "Learning to Ground Multi-Agent Communication with Autoencoders"
mycal-tucker/mlm_dropout_probes
mycal-tucker/mycal-tucker.github.io
my personal website
mycal-tucker/parole
Analysis of parole hearings in NYC, based on initial code from https://github.com/rcackerman/parole-hearing-data
mycal-tucker/PPLM
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
mycal-tucker/skill-sample-nodejs-fact
Build An Alexa Fact Skill
mycal-tucker/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
mycal-tucker/UD_French-GSD
mycal-tucker/VizDoom-Keras-RL
Reinforcement Learning in Keras on VizDoom
mycal-tucker/vqvae
A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)