Rico贾若童的博客

[ML] D-PCC Losses

Chamfer Loss, Density Loss, Point-Count Loss, Rate-Distortion Loss

Entropy Encoding What is the bottleneck? In learned compression the entropy bottleneck is a learned probability model $p(\hat{z})$ placed on the quantized latent features $\hat{z}$. It serves two...

Posted by Rico's Nerd Cluster on February 11, 2026

Entropy Bottleneck

Entropy Encoding, Range Encoding

Problem Setup Suppose one encoder output (latent vector) is z = [0.13, -1.82, 0.07]. Storing these as float32 costs $3 \times 32 = 96$ bits. Entropy coding requires discrete symbols, so we first q...

Posted by Rico's Nerd Cluster on February 8, 2026

[ML] D-PCC Decoder Layers

isohedron, losses

Decoder Overview The overall decoder is looking to achieve the below: Icosahedron vertices on a unit sphere become candidate directions — unit vectors pointing from a...

Posted by Rico's Nerd Cluster on February 6, 2026

[ML] D-PCC Encoder-Layers

sub-pixel convolution

D-PCC paper Terminology latent feature: a compressed internal representation that contains essential information needed to reconstruct the original data. Cardinality: the number of elements ...

Posted by Rico's Nerd Cluster on February 3, 2026

[ML] Point Cloud Transformer

Vector Attention

Terminology modulate In ML, modulation means changing one signal using another signal. So Attention $output=\alpha \odot v$ with elementwise product is modulation on value fea...

Posted by Rico's Nerd Cluster on February 2, 2026

[ML] OpenClaw

OpenClaw Video: https://www.youtube.com/watch?v=Otn-NbpQH1k Start Ollama: 1 2 3 4 5 6 ollama run http://localhost:11434/ ollama launch openclaw # on the control panel /model qwen2.5:7b...

Posted by Rico's Nerd Cluster on February 1, 2026

[ML] Data Formats

Pickle, pth, onnx

Pickle A Python serialization format for saving objects to disk and loading them back later. Common use cases include models, dictionaries, lists, pandas DataFrames, preprocessing objects, and int...

Posted by Rico's Nerd Cluster on January 23, 2026

[CUDA - 6] CUDA Functions

attomicAdd, pragma unroll

atomicAdd There’s no such thing as “atomic memory” in CUDA—atomicity is a property of an operation, not a memory type. atomicAdd is an instruction you apply to a memory location (typically in glob...

Posted by Rico's Nerd Cluster on January 21, 2026

[CUDA - 5] SIMT in CUDA

SIMD SIMT

SIMT and SIMD CUDA is a very good embodiment of SIMD (Single-Instruction-Multiple Data). SIMD is great for addressing embarassingly parallel problems, problems that are so “embarassingly” simple, ...

Posted by Rico's Nerd Cluster on January 19, 2026

[CUDA - 4] My First CUDA Kernel - Chamfer Distance

First CUDA Program, JIT Compile

On Chamfer Distance Chamfer distance measures how close two point clouds are by averaging nearest-neighbor distances in both directions. Given two point sets $P_1$ and $P_2$, For each point ...

Posted by Rico's Nerd Cluster on January 18, 2026

Rico's Nerd Cluster