An Implementation of Deep Q Network using TensorFlow
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Updated
Nov 12, 2018 - Python
An Implementation of Deep Q Network using TensorFlow
Memory-efficient probabilistic counter namely Morris Counter
Train Dense Passage Retriever (DPR) with a single GPU
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
A fast, efficient universal vector embedding utility package.
A lightweight and memory-efficient HTTP client module for MicroPython, optimized for use cases on resource-constrained devices such as ESP32.
The official implementation of "CAME: Confidence-guided Adaptive Memory Optimization"
The official implementation of MeDQN algorithm.
Code for: "Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation" Accepted @ ECCV2022
Transformers with Arbitrarily Large Context
Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT
Official PyTorch implementation of the CVPRW 2023 paper
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