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Decision Making

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/pladosz/MOHQA

공식 코드

Deep Reinforcement Learning with Modulated Hebbian plus Q Network Architecture

https://github.com/plai-group/a2d

공식 코드

Robust Asymmetric Learning in POMDPs

https://github.com/plankson/csirl

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Curricular Subgoals for Inverse Reinforcement Learning

https://github.com/plead-project/ebd-artefacts

공식 코드

A Methodology and Software Architecture to Support Explainability-by-Design

https://github.com/pliang279/LM_bias

공식 코드

Towards Understanding and Mitigating Social Biases in Language Models

https://github.com/pmineiro/linrepcb

공식 코드

Contextual Bandits with Large Action Spaces: Made Practical

https://github.com/pmm09c/ntire-dehazing

공식 코드

Feature Forwarding for Efficient Single Image Dehazing

https://github.com/pnnl/deps_arXiv2020

공식 코드

Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees

https://github.com/pnnl/neuromancer

공식 코드

Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees

https://github.com/pnokhiz/precarity

공식 코드

Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instability

https://github.com/poetrywanderer/CF-NeRF

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Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification

https://github.com/pointW/equidiff

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Equivariant Diffusion Policy

https://github.com/pointscoder/gpt-driver

공식 코드

GPT-Driver: Learning to Drive with GPT

https://github.com/portal-cornell/orca

공식 코드

Imitation Learning from a Single Temporally Misaligned Video

https://github.com/pouriagr/deep-cover

공식 코드

DeepCover: Advancing RNN Test Coverage and Online Error Prediction using State Machine Extraction

https://github.com/pouriamrt/BHI_chatbot

공식 코드

An AI-Driven Live Systematic Reviews in the Brain-Heart Interconnectome: Minimizing Research Waste and Advancing Evidence Synthesis

https://github.com/pouriarouzrokh/lattereview

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LatteReview: A Multi-Agent Framework for Systematic Review Automation Using Large Language Models

https://github.com/pouyaAB/Accept_Synthetic_Objects_as_Real

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Accept Synthetic Objects as Real: End-to-End Training of Attentive Deep Visuomotor Policies for Manipulation in Clutter

https://github.com/praal/remembering-to-be-fair

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Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making

https://github.com/prabaey/nbn-understudy

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Neural Bayesian Network Understudy

https://github.com/prabhath-r/FDQN_RL

공식 코드

FDQN: A Flexible Deep Q-Network Framework for Game Automation

https://github.com/prabin525/spatial-llm

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Are Large Language Models Geospatially Knowledgeable?

https://github.com/pradyut3501/spurious_corr

공식 코드

LoRA Users Beware: A Few Spurious Tokens Can Manipulate Your Finetuned Model

https://github.com/prajjwal1/rl_paradigm

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When should we prefer Decision Transformers for Offline Reinforcement Learning?

https://github.com/pralab/UncertaintyAdversarialRobustness

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On the Robustness of Adversarial Training Against Uncertainty Attacks

https://github.com/pranavphoenix/Backbones

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Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision

https://github.com/praveenchopra/ProgressiveSpinalNet

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ProgressiveSpinalNet architecture for FC layers

https://github.com/predict-idlab/cct-cmc

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Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects

https://github.com/predict-idlab/cmc-learner

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Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects

https://github.com/predict-idlab/crepes-weighted

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Conformal Predictive Systems Under Covariate Shift

https://github.com/predict-idlab/dose-response-conformal-prediction

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Conformal Prediction for Dose-Response Models with Continuous Treatments

https://github.com/predopt/predopt-benchmarks

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Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

https://github.com/preethisesh/hiring_fairness

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Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring Contexts

https://github.com/premiertaco/premier-taco

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Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss

https://github.com/prescient-design/lobster

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Concept Bottleneck Language Models For protein design

https://github.com/previtus/ravaen-unibap-dorbit

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Fast model inference and training on-board of Satellites

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