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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,878 papers · 148 categories

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1122 · Sep 201919922001200920172026
12 results for Bidirectional-RNN

Delayed-RNN approximates stacked and bidirectional RNNs.

problem Improving RNN expressiveness and representational capacity.
method Weight-constrained delayed-RNN, equivalent to stacked-RNNs, with partial acausality.
result Delayed-RNN can approximate stacked and bidirectional RNNs, outperforming them in some tasks.

BiHRNN predicts inflation by leveraging hierarchical structure and bidirectional RNNs.

problem Accurate inflation forecasting is challenging due to dynamic factors and the layered structure of the Consumer Price Index.
method Bi-directional Hierarchical Recurrent Neural Network (BiHRNN) model that uses bidirectional information flow between levels and informative constraints on RNN parameters.
result BiHRNN significantly outperforms traditional RNN models in forecasting accuracy.

GEN generates millions of valid SMILES with high novelty and property conservation.

problem Generating high-quality, de novo molecules in a known chemical space.
method GEN uses bidirectional RNNs with concatenated sub-models to learn and generate SMILES, with online examination to ensure quality.
result GEN can generate SMILES with 95-98% validity, 85-90% novelty, and 95-99% property conservation.

Study proves deep narrow RNNs can approximate any function, with minimum width independent of data length.

problem Proving universality of deep narrow RNNs with bounded widths.
method Analyzing RNNs as dynamical systems, proving universality for deep narrow structures with specific widths.
result Minimum width for universality of deep narrow RNNs is independent of data length.

PLUS pre-trains protein sequences with structural info, improving performance.

problem Lack of labeled protein sequences for training models.
method PLUS combines masked language modeling with same-family prediction for pre-training.
result PLUS-RNN outperforms other models in protein biology tasks.