-
Philosophy Lives
-
The Unreasonable Difficulty of Time Series Forecasting
-
Grief of a Craftsman
-
(Production) Logging for AI Agents
-
High variance in RL (and how to measure it)
-
MCP without analogies
-
Reproducing GPT2-125M
-
Middle Aged Work Advice
-
Dynamic Batching for Training Large Sequence Models (LLMs)
-
RAG System Architecture
-
Vibe Coding Car Racing Simulator (Fail)
-
Deriving the Basic Policy Gradient Update (REINFORCE)
-
Data Extraction for Unstructured Document Data
-
First 100 words
-
Temporal Difference Learning: Taking advantage of Incomplete Trajectories
-
Synthetic Question Generation for Retrieval Evaluation of RAG
-
Deriving the minimax equation for GANs
-
Chunking code for RAG; parsing-recursion-stack
-
A classical NLP researcher and a GPT-era Engineer meet at the coffee machine
-
Python Decorators for Monitoring GPU Usage
-
A baby and a PhD
-
LLM Research and Adaptation Landscape
-
Monitoring Jobs on the Server
-
Taking a break from NLP Research
-
Lean OmegaConf Argparse System
-
Training Sparse Neural Networks with L0 Regularisation
-
Dynamic Programming for Reinforcement Learning, the importance of the Bellman equations; (with Gymnasium)
-
Could Large Language Models be conscious? (David Chalmers @ Neurips 2022)
-
NLP Papers at ICML2022
-
You don't feel like you're good enough, but its not a competition
-
Stochastic Gradient Langevin Dynamics
-
NYCMidnight-100words
-
Recipe for connecting to Google Drive from Remote Server
-
Minimum Bayes Risk Decoding
-
Formalising Analogies for A.I
-
You're not doing well, but motivation is optional
-
Likelihood weighted Sequential Importance Sampling
-
Neural Tangent Kernel, Every Model trained by GD is a kernel machine (Review)
-
Some QA from Deep Learning (CS 462/482)
-
NEURIPS 2020
-
Adversarial NLP examples with Fast Gradient Sign Method
-
EMNLP 2020
-
Variance of the Estimator in Machine Learning
-
Some Clustering Papers at ICLR20
-
A minimum keystroke (py)Debugger for Lazy ML/DS people who don't IDE
-
Recipe for building jq from source without admin(sudo) rights
-
The Sigmoid in Regression, Neural Network Activation and LSTM Gates
-
Arithmetic(Book)
-
Clean TreeLSTMs implementation in PyTorch using NLTK treepositions and Easy-First Parsing
-
Pad pack sequences for Pytorch batch processing with DataLoader
-
Modes of Convergence
-
Coordinate Ascent Mean-field Variational Inference (Univariate Gaussian Example)
-
Dirichlet Process Gaussian Mixture Models (Generation)
-
Gotchas in Cython; Handling numpy arrays in cython class
-
Onboarding for Practical Machine Learning Research
-
Equivalence of constrained and unconstrained form for Ridge Regression
-
Studying drug-drug interactions and predictors of adverse vascular outcomes
-
PyTorch Automatic differentiation for non-scalar variables; Reconstructing the Jacobian
-
From psychologist to CS PhD Student
-
Capturing Last-mile Transactions of Smallholder Palm Oil Farmers
-
Migrating from python 2.7 to python 3 (and maintaining compatibility)
-
Lagrange Multipliers and Constrained Optimization
-
Taylor Series approximation, newton's method and optimization
-
Hessian, second order derivatives, convexity, and saddle points
-
Jacobian, Chain rule and backpropagation
-
Gradients, partial derivatives, directional derivatives, and gradient descent
-
Derivatives, differentiability and loss functions
-
Calculus for Machine Learning
-
Algorithms on Graphs: Fastest Route
-
Gibbs Sampling on Dirichlet Multinomial Naive Bayes (Text)
-
Markov Chain Monte-Carlo
-
EM Algorithm for Gaussian mixtures
-
Communicating Data Science
-
Cross disciplinary projects
-
Conjugate Priors
-
Closed form Bayesian Inference for Binomial distributions
-
DSO Advice
subscribe via RSS