Popular GitHub Repositories for Induced Polarization

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

Official Pytorch implementation of PANDORA: Polarization-Aided Neural Decomposition of Radiance

Code & Data for our Paper "Alleviating Hallucinations of Large Language Models through Induced Hallucinations"

An implementation of (Induced) Set Attention Block, from the Set Transformers paper

The code of paper Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion. Zhanqiu Zhang, Jianyu Cai, Jie Wang. NeurIPS 2020.

XLuminA, a highly-efficient, auto-differentiating discovery framework for super-resolution microscopy.

[KDD 2024] "ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation"

[ICLR 2025] Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality

Training for multi-modal image fusion with PyTorch.

Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification (WWW'22)

[ICML 2023] Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

Hypergraph-Induced Semantic Tuplet Loss for Deep Metric Learning [CVPR'22]

PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations

Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)

BISIP | Bayesian inversion of spectral induced polarization laboratory data

Official repository for SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment.

Official PyTorch implementation of "TridentAdapt: Learning Domain-invariance via Source-Target Confrontation and Self-induced Cross-domain Augmentation"

PyTorch implementation of the time-domain induced polarization variational autoencoder

Time Series Analyses and Machine Learning for Classifying Events prior to Fiber Cuts

DeepEthos is a research framework that analyzes how different AI models approach ethical reasoning. It systematically tests OpenAI, Anthropic, and Google models across multiple ethical scenarios, comparing standard, Chain-of-Thought, and induced reasoning approaches.