Yuzhe Yang

Hi @ttsesm Yes - that could serve as an example! - The core code for LDS is basically here: https://github.com/YyzHarry/imbalanced-regression/blob/main/agedb-dir/datasets.py#L55, where we estimate a weight for each sample based on...

Hi @snigdhasen Yes, I believe that is a complete codebase, and you might only need to modify the data loading part (and maybe the network you choose to use).

@ttsesm Sorry for the late reply! > Now the question is how to apply LDS/FDS based on the values in column 4. Is this done before you load the data...

> What is the difference between the two re-weighting options i.e. `inv` and `sqrt_inv`, and why should I choose one over the other? Actually, we use `sqrt_inv` by default for...

Hi @snigdhasen It seems the loss is gradually decreasing (though very slow). I guess the value in the parentheses is the average value for MSE/L1 loss.

Hi @zhaosongyi - this is an interesting point. In our work, we use a symmetric kernel since we assume the distance with respect to an anchor point in the target...

Thanks for your interest. > characteristic statistics of each label interval are particularly similar Seems to me the network does not learn discriminative features in the first place. Maybe you...

Hi, thanks for your interest! We provided experiment results of MoCo on CIFAR in Appendix Table 9 of our [paper](https://arxiv.org/pdf/2006.07529.pdf). It could bring improvements over the baseline, but is not...

Hi - thank you for your interest! Sorry for the late reply as there were some major deadlines around. For your question, the overall answer should be mostly yes ---...

Hi - thanks for your interest. The base model is obtained by normal training procedure on the labeled imbalanced dataset. You can also customize the base loss function or training...