Soumik Rakshit

PoE-GAN is a recent, fascinating paper where the authors generate images from multiple inputs like text, style, segmentation, and sketch. We dig into the architecture, the underlying math, and of course, generate some images along the way.

Or, teaching four-legged robots to walk in the real world

Representing large city-scale environments spanning multiple blocks using Neural Radiance Fields

Robust and high-precision semantic image editing in real-time

A novel GAN-based optimization method for photo-realistic hairstyle transfer

This article uses JAX to create a minimal implementation of 3D volumetric rendering of scenes represented by Neural Radiance Fields, using W&B to track all metrics.

In this article, we'll explore a novel and efficient approach for joint optimization of topology, materials, and lighting from multi-view image observations.

In this article, we explore how to achieve photorealistic rendering of large unbounded 3D scenes from novel camera angles while preserving fine-grained details.

In this article, we revisit evolutionary strategy algorithms for computational creativity and look at how they improve quality and efficiency in generating art.

In this article, we take a deep dive into how StyleGAN-NADA achieved the task of CLIP-guided domain adaptation and explore how we can use the model itself.

In this article, we explore an end-to-end training and evaluation pipeline in JAX, Flax, and Optax for image classification, using W&B to track experiments.

A short tutorial on leveraging Weights & Biases to train a semantic segmentation model for autonomous vehicles.

Digging into object detection and perception for autonomous vehicles using YOLOv5 and Weights & Biases

A primer on text-driven image editing for large-scale text-based image synthesis models like Stable Diffusion & Imagen

An introduction to building an Image Restoration model using Tensorflow, Keras, and Weights & Biases.

In this article, we explore how to train unconditional image generation models using HuggingFace Diffusers and we will track these experiments and compare the results usingWeights & Biases.

In this article, we explore the paper "Fast Text-Conditional Discrete Denoising on Vector-Quantized Latent Spaces" which introduces Paella, a novel text-to-image model.

This article explores creating accurate, fast approximations of complex 3D scenes with a low memory footprint, as outlined in 'Variable Bitrate Neural Fields'.

Exploring how Depthwise Separable Convolutions can make CNNs faster

In this article, we explore how to classify point cloud data from 3D CAD Models, implementing the PointNet++ architecture and using PyTorch Geometric and W&B.

In this article, we dive into the ShapeNetCore Dataset for the classification and segmentation of point cloud data and explore how to use it using Weights & Biases.

In this article, we explore a simple point cloud segmentation pipeline using Dynamic Graph CNNs, implemented using PyTorch Geometric along with Weights & Biases.

In this article, we explore DeepFloydAI — an AI Research Band which is working with StabilityAI to make AI open again.

In this article, we quickly teach Stable Diffusion new visual concepts using Dreambooth in Keras, to produce fully-novel photorealistic images of a given subject.

In this article, we explore some deep learning techniques for low-light image enhancement, so that you can enhance images taken under sub-optimal conditions.

A set of comprehensive benchmarks around XLA compatibility of computer vision models implemented in Keras.

A guide on using Weights & Biases with Ultralytics workflows for computer vision models

A comprehensive guide to using Stable Diffusion XL (SDXL) for generating high-quality images using HuggingFace Diffusers and managing experiments with Weights & Biases

This article provides a comprehensive guide to using state-of-the-art music and audio generation models using AudioCraft from Meta, along with Weights & Biases.

A comprehensive guide to fine-tuning a pre-trained model from TorchVision using Keras.

A comprehensive guide to building an object detection workflow using Ultralytics YOLOv8 and Weights & Biases.

A comprehensive guide to prompt engineering for generating images using Stable Diffusion, HuggingFace Diffusers and Weights & Biases.

This article provides a short tutorial on how to run experiments with Pixart-α — the new transformer-based Diffusion model for generating photorealistic images from text.

Supercharging your Deep Learning workflows for Medical Imaging using MonAI and Weights & Biases

Today, we're going to leverage a RAG pipeline to create an AI TA capable of helping out with grading, questions about a class syllabus, and more

Learn how to use DSPy teleprompters and Weave to automatically optimize prompting strategies for causal reasoning

This article shows the implementation of an LLM-assisted prompt upsampling strategy to improve the quality of images generated by Stable Diffusion.

Until September 27th Weights & Biases users can illustrate their own stories for free using Flux and GPT-4

Understanding SEC filings with the help of foundation models