Repo for Yale Applied Empirical Methods PHD Course

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

mixup: Beyond Empirical Risk Minimization

An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

Python implementation of Empirical Mode Decompoisition (EMD) method

Readex Pro is the world-script expansion of Lexend. Lexend is a variable font empirically shown to significantly improve reading-proficiency.

Can large language models provide useful feedback on research papers? A large-scale empirical analysis.

The repository for the largest and most comprehensive empirical study of visual foundation models for Embodied AI (EAI).

A comprehensive list [SAMRS@NeurIPS'23, RVSA@TGRS'22, RSP@TGRS'22] of our research works related to remote sensing, including papers, codes, and citations. Note: The repo for [TGRS'22] "An Empirical Study of Remote Sensing Pretraining" has been moved to: https://github.com/ViTAE-Transformer/RSP

How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study

A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...

An empirical study on evaluation metrics of generative adversarial networks.

Tools and standards for conducting and evaluating research in software engineering

Implementation for OAgents: An Empirical Study of Building Effective Agents

An implementation of "mixup: Beyond Empirical Risk Minimization"

Empirical tricks for training robust models (ICLR 2021)

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.

Graduate Empirical Industrial Organization

[ICCV 2025] Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives

This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data

Introduction to Empirical Bayes: Examples from Baseball Statistics

Python library that represents empirical distribution functions.

A language for time-series analysis

Test and evaluate LLMs and model configurations, across all the scenarios that matter for your application

[COLM 2025] Assessing Judging Bias in Large Reasoning Models: An Empirical Study https://openreview.net/pdf?id=SlRtFwBdzP

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking. (NeurIPS 2024)

The official repo for [TGRS'22] "An Empirical Study of Remote Sensing Pretraining"

To classify trades into buyer- and seller-initiated.

[ICLR 2025] When Attention Sink Emerges in Language Models: An Empirical View (Spotlight)

ACL 2022: An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models.