Search Results for author:
Found 10 papers, 9 papers with code
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Above all, we consider the introduction of a completely new type of solution to be our most important contribution as it may spark entirely new innovations in treatment effects in general.
Retrieval-Augmented Thought Process as Sequential Decision Making
Large Language Models (LLMs) have demonstrated their strong ability to assist people and show "sparks of intelligence".
Dense Reward for Free in Reinforcement Learning from Human Feedback
Reinforcement Learning from Human Feedback (RLHF) has been credited as the key advance that has allowed Large Language Models (LLMs) to effectively follow instructions and produce useful assistance.
Deep Generative Symbolic Regression
Symbolic regression (SR) aims to discover concise closed-form mathematical equations from data, a task fundamental to scientific discovery.
L2MAC: Large Language Model Automatic Computer for Extensive Code Generation
Transformer-based large language models (LLMs) are constrained by the fixed context window of the underlying transformer architecture, hindering their ability to produce long and coherent outputs.
Ranked #3 on
Code Generation
on HumanEval
Neural Laplace Control for Continuous-time Delayed Systems
Many real-world offline reinforcement learning (RL) problems involve continuous-time environments with delays.
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain
Neural Ordinary Differential Equations model dynamical systems with ODEs learned by neural networks.
Fear and Volatility in Digital Assets
We show Bitcoin implied volatility on a 5 minute time horizon is modestly predictable from price, volatility momentum and alternative data including sentiment and engagement.
Deep Learning for Digital Asset Limit Order Books
This paper shows that temporal CNNs accurately predict bitcoin spot price movements from limit order book data.
Statistical Finance
A Decade of Evidence of Trend Following Investing in Cryptocurrencies
Cryptocurrency markets have many of the characteristics of 20th century commodities markets, making them an attractive candidate for trend following strategies.
