Multilayer NLAs
use multi-layer inputs for your natural language autoencoders.
cat ./projects.md
Stuff I've tinkered with.
use multi-layer inputs for your natural language autoencoders.
mechanistic study of racial and gender bias in gpt-2 and gpt-neo using linear probes, activation patching, attribution patching, and circuit tracing. steered model outputs to show reduced bias without MMLU degredation.
an end-to-end tour through SfM, MVS, GANs, neural radiance fields, and gaussian splatting for reconstructing scenes from images.
a comparative analysis of traditional machine-learning classifier systems for face recognition on the LFW dataset.
Moshi-based duplex conversational agent that utilizes audio (micrsoft S5) and visual (QuantumConv) contexts to provide real-time stress counseling.
flow-based, diffeomorphic generative models for deep-learning based particle-shower simulation in cylindirical coordinates for high-energy physics.
byzantine fault tolerance in peer-to-peer networks, simulated with OMNeT++.
a mini file-compression system built around Huffman coding.