Code of our winning entry to NTIRE super-resolution challenge, CVPR 2018

RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).

If you are a newbie in coding and wanna do CP then first solve this DSA question then move to cp..it will surely gonna help u clear the concepts. and get better at cp.

Computationally efficient rolling window iterators for Python (sum, variance, min/max, etc.)

Official code for our ECCV'22 paper "A Fast Knowledge Distillation Framework for Visual Recognition"

EDCC: An efficient and accurate algorithm for palmprint recognition.

PeleeNet: An efficient DenseNet architecture for mobile devices

This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.

[ICML 2026] d3LLM: Ultra-Fast Diffusion LLM 🚀

Coursera's Data Structures and Algorithms Specialization

Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-Identification (BMVC 2019)

Official Code for Paper: Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation

Resources of our survey paper "Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System Strategies"

This is our implementation of EHCF: Efficient Heterogeneous Collaborative Filtering (AAAI 2020)

[ICLR 2026 Oral] Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

Shared-memory parallel minimum cut algorithms (inexact, exact, cactus, multiterminal)

the Pedestrian_graph_plus implementation

This is our implementation of ENSFM: Efficient Non-Sampling Factorization Machines (WWW 2020)

This is our implementation of EATNN: Efficient Adaptive Transfer Neural Network (SIGIR 2019)

This is our implementation of JNSKR: Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation (SIGIR 2020)