DenseNet implementation in Keras
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Updated
Jun 10, 2020 - Python
DenseNet implementation in Keras
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks
Tensorflow implementation of deep variational information bottleneck
🐼PANDA: Expanded Width-Aware Message Passing Beyond Rewiring, ICML 2024
simple ABM program to simulate a moving danger (e.g., fire) and people in a confined space trying to escape the danger
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
Method to estimate the age and intensity of recent bottlenecks/founder events, using genotype data and a recombination map.
Visualize the Latent Space of an Autoencoder using matplotlib
⭐⭐⭐ Pytorch implementation of Attentiom, Backbone, ViT, MLP, Re-parameter, Convolution, very flexible module combination.
Python-based code for estimation of highway bottleneck probability using speed transition matrices.
A PyTorch toolkit for 2D Human Pose Estimation.
single-file "bottle.py" , a website-application µ framework
Offline, fail-closed verifier for JSONL telemetry event logs. Emits deterministic audit certificates + human summaries with explicit claims/non-claims for bottleneck and integrity review.
A Keras implementation of YOLOv3 (Tensorflow backend)
Chrome DevTools trace and heap snapshot analyzer that converts raw performance data into actionable diagnostics and remediation guidance.
A research Python simulation of evolving human-like color naming via Information Bottleneck and replicator dynamics, benchmarked on a 50-participant survey and five perceptual environments to explore efficiency-complexity trade-offs.
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