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CreateAMind

专栏成员
986
文章
614204
阅读量
56
订阅数
解决Bongard问题:一种强化学习因果方法,2022
Towards a solution to bongard problems: A causal approach
CreateAMind
2024-06-21
380
dreamcoder-arc:用于抽象和推理的神经网络 ARC-AGI
Neural networks for abstraction and reasoning:Towards broad generalization in machines用于抽象和推理的神经网络:机器的广义泛化
CreateAMind
2024-06-21
1420
朱松纯团队2019:RAVEN ; and I-RAVEN
Stratified Rule-Aware Network for Abstract Visual Reasoning
CreateAMind
2024-06-21
640
朱松纯团队2021: 通过概率推理和执行进行抽象时空推理
Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Execution通过概率推理和执行进行抽象时空推理
CreateAMind
2024-06-19
810
使用归纳逻辑编程解决抽象和推理测试,ARC
Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus使用归纳逻辑编程的抽象和推理语料库的程序综合
CreateAMind
2024-06-18
670
Bengio:实现AGI的主要原则已经被发现?剩下的主要障碍是扩大规模?还是。。
Inductive biases for deep learning of higher-level cognition 高级认知深度学习的归纳偏差
CreateAMind
2024-06-17
600
定义智能,测量智能
On the Measure of Intelligence https://arxiv.org/abs/1911.01547
CreateAMind
2024-06-17
1050
定义智能: Bridging the gap between human and artificial perspectives
Defining intelligence: Bridging the gap between human and artificial perspectives
CreateAMind
2024-06-17
700
Bengio2310:以对象为中心的架构支持高效的因果表示学习
Object-centric architectures enable efficient causal representation learning以对象为中心的架构支持高效的因果表示学习
CreateAMind
2024-06-17
570
关注背景信息的运动物体发现
The Background Also Matters: Background-Aware Motion-Guided Objects Discovery
CreateAMind
2024-06-05
460
概率电路+医疗领域知识的统一学习框架
A Unified Framework for Human-Allied Learning of Probabilistic Circuits
CreateAMind
2024-06-04
480
Object-Centric:Faster Attend-Infer-Repeat 2019,场景理解建模思路2
Faster Attend-Infer-Repeat with Tractable Probabilistic Models利用易处理的概率模型加快注意-推断-重复 http://proceedings.mlr.press/v97/stelzner19a/stelzner19a.pdf
CreateAMind
2024-06-04
890
形态发生作为贝叶斯推理:复杂生物系统中模式形成和控制的变分方法
Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems 2020
CreateAMind
2024-06-04
1320
超GFlowNet 4个数量级加速
https://github.com/PrincetonLIPS/MaM https://arxiv.org/pdf/2310.12920
CreateAMind
2024-06-04
570
神经网络轻松表示任意复杂度的贝叶斯后验的能力预示着科学数据分析的一场革命2
Consistency Models for Scalable and Fast Simulation-Based Inference
CreateAMind
2024-06-04
1411
主动推理、形态发生和计算精神病学
Active inference, morphogenesis, and computational psychiatry
CreateAMind
2024-06-04
830
概率建模和推理的标准化流 review2021
Normalizing Flows for Probabilistic Modeling and Inference 调查
CreateAMind
2024-06-04
1000
基于仿真的推理前沿(SBI2019)
The frontier of simulation-based inference基于仿真的推理前沿
CreateAMind
2024-06-04
560
从嘈杂数据中推断复杂模型的参数:CMPE
Consistency Models for Scalable and Fast Simulation-Based Inference
CreateAMind
2024-06-04
1011
仿真智能: 新一代的科学方法
Simulation Intelligence: Towards a New Generation of Scientific Methods https://arxiv.org/abs/2112.03235
CreateAMind
2024-06-04
1280
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