[D] Calling out the authors of 'Trajformer' paper for claiming they published code but never doing it

• Trajformer

  2 37 0.0 Python

  Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving (NeurIPS 2020)

I read a paper from NeurIPS 2020 titled 'Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving'. I found it interesting and the authors claim multiple times in the paper that 'we release our code at 'https://github.com/Manojbhat09/Trajformer'. Turns out they never did, fine, I thought perhaps they will in the future and starred the repo to check it out later.

• community

  3 1,242 6.9 C++

  Stores documents used by the TensorFlow developer community (by tensorflow)

  

Most things leveraging CUDA/CuDNN/CuBLAS without explicit effort to keep it deterministic. E.g. Convolution and Pooling in PyTorch on the GPU and the same in TensorFlow

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• CASD

  1 84 1.8 Python
  

In my experience, the kinds of people who are worried about their code quality are usually aware enough that there isn't any major flaws that would invalidate a finding. The ones with fundamental flaws aren't so self-aware. E.g. This one, which out-performs their published result whilst not including a working implementation of their novel contribution

• CMU-DATF

  1 2 0.0 Python

We used the dataset referred from this paper: https://arxiv.org/abs/2003.03212. and root codebase https://github.com/Manojbhat09/CMU-DATF

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