Datasets:
File size: 1,264 Bytes
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---
language:
- en
license: mit
task_categories:
- time-series-forecasting
dataset_info:
features:
- name: t
dtype:
array2_d:
shape:
- 1001
- 1
dtype: float64
- name: x
dtype:
array2_d:
shape:
- 1001
- 900
dtype: float64
- name: args
dtype:
array2_d:
shape:
- 1001
- 1
dtype: float64
splits:
- name: train
num_bytes: 4413496400
num_examples: 610
- name: valid
num_bytes: 795876400
num_examples: 110
- name: test_fast
num_bytes: 3617620000
num_examples: 500
- name: test_medium
num_bytes: 3617620000
num_examples: 500
- name: test_slow
num_bytes: 3617620000
num_examples: 500
download_size: 14279999184
dataset_size: 16062232800
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test_fast
path: data/test_fast-*
- split: test_medium
path: data/test_medium-*
- split: test_slow
path: data/test_slow-*
---
# Dataset for polymer dynamics
References
- Chen, X. et al. Constructing custom thermodynamics using deep learning. Nature Computational Science 4, 66–85 (2024).
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