sha1_base64="aabjZM6SNm3NlwPbE7sqkAWyXzk=">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</latexit> ♷ִ㣐ꆀךⰅ⳿⸂ך鋅劤⢽ⱄ植דֹ״ֲזⰅ⸂ַ⳿⸂פ ך㢌䳔فؚٗٓيꬊ僇爙涸ח欰䧭ׅך害欽涸倯岀 ♧菙暟⡤钠陎 갈㡮钠陎 堣唒缺鏬 馄鍑⫷؎ً٦آؚٝ ⴓ㶨ך嫩䚍✮庠 ˑָ֮הֲ˒ J’aime la musique I love music CH3 N H 3 C H N S N O CH3 N OH 1.394
in-praise-of-boring-ai-a-k-a-machine-learning/ ʜ “Let’s face it: So far, the artificial intelligence plastered all over PowerPoint slides hasn’t lived up to its hype.” The AI frenzy: hope & hype
<latexit sha1_base64="QFtMwnKe2I12XGZu0bNJbdnDaaE=">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</latexit> x2 <latexit sha1_base64="lFhRrRrVTrFR31ebbMgRp5myJpc=">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</latexit> x3 <latexit sha1_base64="0IPXcU0UIDvzZlYURjV2A/THv9U=">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</latexit> . . . Latent variables Learnable variable transformation Representation learning Classifier or Regressor Linear <latexit sha1_base64="Ill3Als4zZd947f5Xm9sW99d0QA=">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</latexit> x1 Simple model is enough when we have good features. 剑鵚ך帾㾴㷕统דכ㔐䌓٥ⴓ겲ךח葺ְ悵㖈㢌侧邌植פך㢌䳔遤ֲ אךـٗحؙךさ䧭ꟼ侧ؿ؍حذ؍ؚٝה׃ג♧孡鸐顐ד剑黝⻉ׅ
potency • Endocrine disruption • Growth inhibition • Aqueous solubility N NH O O H H H H H H H H H H H H H H H H H H H H H H H H H O O O O O O Cl H H H H H H H H H H H H H H H H H Br Br O P O O Br Br O Br Br H H H H H H H H H H H H H H H N S N N H H H H H H H H H H H H H H H O N O O H H H O O H H N O O Cl Cl Cl H H H H H H H N O O H H H H H H H H H N O O H H H H H H H N H N O O N O O H H H H H H H H N CH3 O O H N Cl Cl Cl Cl Cl H 3 C O O O O O O H 3 C CH3 CH2 O HN O O NH CH3 HO OH CH 3 N O O CH 3 N N H N H H 3 C N H 3 C H 3 C NH O N O N O CH3 O N NH 2 O CH3 Br CH3 N H 3 C H N S N O CH3 N OH CH3 CH3 N N N CH3 H 3 C H2 N NH2 H OH O HO CH 3 H H O CH 3 H O O H 3 C H H H O H 3 C S CH3 O H H O CH3 CH3 O O HO H 3 C H HO F H O H 3 C NH 2 O N HO H O O H H O O O H 3 C O O O CH 3 O CH 3 H O CH 3 H O O CH 3 H H N H N O H 3 C O O O
C H H H H H N O C C C C H H H H H GNN Layer GNN updates features <latexit sha1_base64="+I1ZH8a510AHL/VRK05INyOdDHc=">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</latexit> hi <latexit sha1_base64="iVE2zwSrY7uMFp5lULN8y4s7ZXg=">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</latexit> eij atom features bond features
C H H H H H N O C C C C H H H H H GNN Layer GNN updates features <latexit sha1_base64="rQGx6XMOvsCjXRp7b9gbmKjgm1M=">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</latexit> hi 0 @hi, M j2Ni (hi, hj, eij) 1 A Update by “Message Passing” <latexit sha1_base64="+I1ZH8a510AHL/VRK05INyOdDHc=">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</latexit> hi <latexit sha1_base64="iVE2zwSrY7uMFp5lULN8y4s7ZXg=">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</latexit> eij atom features bond features
C H H H H H N O C C C C H H H H H GNN Layer GNN updates features Ԯ ԮMessage Permutation equivariant operations • nn.Linear Bond features can be used (typically in Ԯ) <latexit sha1_base64="rQGx6XMOvsCjXRp7b9gbmKjgm1M=">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</latexit> hi 0 @hi, M j2Ni (hi, hj, eij) 1 A Update by “Message Passing” <latexit sha1_base64="+I1ZH8a510AHL/VRK05INyOdDHc=">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</latexit> hi <latexit sha1_base64="iVE2zwSrY7uMFp5lULN8y4s7ZXg=">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</latexit> eij atom features bond features
C H H H H H N O C C C C H H H H H GNN Layer GNN updates features • sum, mean or max • attentive pooling ԯ ԯAggregate Permutation invariant operations Ԯ ԮMessage Permutation equivariant operations • nn.Linear Bond features can be used (typically in Ԯ) <latexit sha1_base64="rQGx6XMOvsCjXRp7b9gbmKjgm1M=">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</latexit> hi 0 @hi, M j2Ni (hi, hj, eij) 1 A Update by “Message Passing” <latexit sha1_base64="+I1ZH8a510AHL/VRK05INyOdDHc=">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</latexit> hi <latexit sha1_base64="iVE2zwSrY7uMFp5lULN8y4s7ZXg=">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</latexit> eij atom features bond features
C H H H H H N O C C C C H H H H H GNN Layer GNN updates features • sum, mean or max • attentive pooling ԯ ԯAggregate Permutation invariant operations Update Any • nn.Linear Ԯ ԮMessage Permutation equivariant operations • nn.Linear Bond features can be used (typically in Ԯ) <latexit sha1_base64="rQGx6XMOvsCjXRp7b9gbmKjgm1M=">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</latexit> hi 0 @hi, M j2Ni (hi, hj, eij) 1 A Update by “Message Passing” <latexit sha1_base64="+I1ZH8a510AHL/VRK05INyOdDHc=">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</latexit> hi <latexit sha1_base64="iVE2zwSrY7uMFp5lULN8y4s7ZXg=">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</latexit> eij atom features bond features
ECFP6(1024) Performance for unseen (test) data: Standard ML GNN Stokes et al, Cell (2020) https://doi.org/10.1016/j.cell.2020.01.021 Marchant, Nature (2020) https://doi.org/10.1038/d41586-020-00018-3 ChemProp (Yang et al, 2019) from MIT MLPDS (Machine Learning for Pharmaceutical Discovery and Synthesis) Consortium Disclaimer: This is just for a toy demo. This should be taken as classification for ACTIVITY_OUTCOME (Active or Inactive) 95.079% (Active/Inactive) 95.604% (Active/Inactive) • Regression for LogGI50 • Regression for LogGI50 • Classification accuracy • Classification accuracy RMSE 0.6076 RMSE 0.7970 Activie/Inactive (Classification), LogGI50 (Regression)
Density Functional Theory (DFT) B3LYP/6-31G(2df, p) <latexit sha1_base64="JI//afsBt1AdIhSgVUbVSGVXtww=">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</latexit> ˆ H = E ⢽ ♧ꨵ㶨晛ך4DISµEJOHFS倯玎䒭 ,PIOˊ4IBN倯玎䒭 ך実鍑 QMܭࢉ
Density Functional Theory (DFT) B3LYP/6-31G(2df, p) <latexit sha1_base64="JI//afsBt1AdIhSgVUbVSGVXtww=">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</latexit> ˆ H = E ⢽ ♧ꨵ㶨晛ך4DISµEJOHFS倯玎䒭 ,PIOˊ4IBN倯玎䒭 ך実鍑 ML 0.01 sec ≈ 100,000 times faster! QMܭࢉ
immediate neighbors who are “heavy” (non-hydrogen) atoms • the valence minus the number of hydrogens • the atomic number • the atomic mass • the atomic charge • the number of attached hydrogens • whether the atom is contained in at least one ring %BZMJHIU ⾱㶨♶㢌ꆀ • hydrogen-bond acceptor or not? • hydrogen-bond donor or not? • negatively ionizable or not? • positively ionizable or not? • aromatic or not? • halogen or not? Rogers and Hahn, JCIM (2005) https://doi.org/10.1021/ci100050t Faber et al, JCTC (2017) https://doi.org/10.1021/acs.jctc.7b00577 .1//ח״ꆀ㶨⻉㷕鎘皾鵚⡂ד欽ְ갥挿٥鴟暴䗙 鸬竲ꆀٓكٕ
et al, 2017) pred vs true for DimeNet (Klicpera et al, 2020) Dipole Moment Energy U HOMO LUMO Heat Capacity Enthalpy H Dipole Moment Energy U HOMO LUMO Heat Capacity Enthalpy H
et al, 2017) pred vs true for DimeNet (Klicpera et al, 2020) Dipole Moment Energy U HOMO LUMO Heat Capacity Enthalpy H Dipole Moment Energy U HOMO LUMO Heat Capacity Enthalpy H ⦓鸞ְז ⼧ⴓ鏩㺁דֹ✮庠铎䊴 ֿכذأزر٦ة 鎮箺儗ח 鋅ׇגזְر٦ة ך穠卓
(Klicpera et al, 2020) Free Energy Free Energy y_true y_true y_pred y_pred ExtraTrees w/ ECFP6 LightGBM w/ ECFP6 3-Layer MLP w/ ECFP6 (without 3D geometry) (without 3D geometry) (without 3D geometry) Free Energy Free Energy Free Energy
⚥呌䪮遭כ䬿挿ꞿ٥歊椚侄䱇ָ涪׃ꆀ㶨⻉㷕鎘皾ח㛇בֻ ⻉㷕䘔穗騟荈⹛䱱稊،ٕ؞ٔؤي S. Maeda, Y. Harabuchi, Exploring paths of chemical transformations in molecular and periodic systems: An approach utilizing force., WIREs Comput. Mol. Sci., 2021, 11, e1538. https://doi.org/10.1002/wcms.1538 ㉀欽晛اؿزؐؑ،ךせח
<latexit sha1_base64="VQOOvVSP0lW6m0gNVQ8zA5pNsEc=">AAAChnichVG7SgNBFD1ZXzE+ErURbIJBsQo3Eh9YBW0sTWJMQCXsrmMcsi92NwEN/oBgq4WVgoX4AX6AjT9gkU8QSwUbC282C6Ki3mV2zpy5586ZuZpjSM8nakeUnt6+/oHoYGxoeGQ0nhgb3/LshquLkm4btlvRVE8Y0hIlX/qGqDiuUE3NEGWtvtbZLzeF60nb2vQPHbFrqjVL7ktd9ZkqulVZTaQoTUEkf4JMCFIIY8NO3GEHe7ChowETAhZ8xgZUePxtIwOCw9wuWsy5jGSwL3CMGGsbnCU4Q2W2zv8ar7ZD1uJ1p6YXqHU+xeDhsjKJGXqkG3qhB7qlJ3r/tVYrqNHxcsiz1tUKpxo/mSy+/asyefZx8Kn607OPfSwHXiV7dwKmcwu9q28enb8UVwozrVm6omf2f0ltuucbWM1X/TovChd/+NHYC78YNyjzvR0/wdZ8OrOYzuazqdxq2KoopjCNOe7HEnJYxwZKXL+GU5zhXIkqaWVBWeqmKpFQM4EvoeQ+AL7mkM4=</latexit> ri <latexit sha1_base64="kTQzD4iiA9afGMFuEz1PlDAJN4Y=">AAAChnichVG7TgJBFD2sL8QHqI2JDZFgrMhgUIwV0caShzwSJGR3HXFlX9ldSJD4Aya2UlhpYmH8AD/Axh+w4BOMJSY2Fl6WTYwS8W5m58yZe+6cmSuZqmI7jHV9wtj4xOSUfzowMzs3HwwtLBZso2HJPC8bqmGVJNHmqqLzvKM4Ki+ZFhc1SeVFqb7X3y82uWUrhn7gtExe0cSarhwrsugQlbOqp9VQhMWYG+FhEPdABF6kjdAjDnEEAzIa0MChwyGsQoRNXxlxMJjEVdAmziKkuPsc5wiQtkFZnDJEYuv0r9Gq7LE6rfs1bVct0ykqDYuUYUTZC7tnPfbMHtgr+/yzVtut0ffSolkaaLlZDV4s5z7+VWk0Ozj5Vo307OAY265XhbybLtO/hTzQN886vdxONtpeY7fsjfzfsC57ohvozXf5LsOz1yP8SOSFXowaFP/djmFQ2IjFt2KJTCKS2vVa5ccKVrFO/UgihX2kkaf6NVziCh3BL8SETSE5SBV8nmYJP0JIfQHBBpDP</latexit> rj EQ1 EQ2 Chemical Reaction
<latexit sha1_base64="VQOOvVSP0lW6m0gNVQ8zA5pNsEc=">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</latexit> ri <latexit sha1_base64="kTQzD4iiA9afGMFuEz1PlDAJN4Y=">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</latexit> rj EQ1 EQ2 Chemical Reaction
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complex procedural behavior, inducing (latent) programs, and reasoning with these programs is a key to solving artificial intelligence. Recently, there have been a lot of success stories in the deep learning community related to learning neural networks capable of using trainable memory abstractions. Neural Abstract Machines & Program Induction • Differentiable Neural Computers / Neural Turing Machines (Graves+ 2014) • Memory Networks (Weston+ 2014) • Pointer Networks (Vinyals+ 2015) • Neural Stacks (Grefenstette+ 2015, Joulin+ 2015) • Hierarchical Attentive Memory (Andrychowicz+ 2016) • Neural Program Interpreters (Reed+ 2016) • Neural Programmer (Neelakantan+ 2016) • DeepCoder (Balog+ 2016) : 䩛竲ֹ涸٥鎸〾涸乼⡲㷕统דֹفؚٗٓيה׃ג䪔ִ״ֲחזגֹ
2020, 2021 • Self-Supervised Graph Transformer on Large-Scale Molecular Data • RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist • Reinforced Molecular Optimization with Neighborhood- Controlled Grammars • Autofocused Oracles for Model-based Design • Barking Up the Right Tree: an Approach to Search over Molecule Synthesis DAGs • On the Equivalence of Molecular Graph Convolution and Molecular Wave Function with Poor Basis Set • CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models • A Graph to Graphs Framework for Retrosynthesis Prediction • Hierarchical Generation of Molecular Graphs using Structural Motifs • Learning to Navigate in Synthetically Accessible Chemical Space Using Reinforcement Learning • Reinforcement Learning for Molecular Design Guided by Quantum Mechanics • Multi-Objective Molecule Generation using Interpretable Substructures • Improving Molecular Design by Stochastic Iterative Target Augmentation • A Generative Model for Molecular Distance Geometry • GraphDF: A Discrete Flow Model for Molecular Graph Generation • An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming • Equivariant message passing for the prediction of tensorial properties and molecular spectra • Learning Gradient Fields for Molecular Conformation Generation • Self-Improved Retrosynthetic Planning • Directional Message Passing for Molecular Graphs • GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation • Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space • A Fair Comparison of Graph Neural Networks for Graph Classification • MARS: Markov Molecular Sampling for Multi-objective Drug Discovery • Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design • Learning Neural Generative Dynamics for Molecular Conformation Generation • Conformation-Guided Molecular Representation with Hamiltonian Neural Networks • Symmetry-Aware Actor-Critic for 3D Molecular Design
excellent review on a very timely subject, which is highly suitable for ACS Catalysis. … I don't usually recommend that papers should be accepted "as is", but in this case I don't see the need for changes. • I will certainly recommend it to my group and my students when it is published. • The manuscript gives an excellent overview in the field of machine learning especially with regard to heterogeneous catalysis and I would highly recommend the article for the publication in ACS Catalysis. • This is one of the best reviews for catalyst informatics that the reviewer has read. In particular, the chapter 2 delivers a very good tutorial, which is concisely and professionally written. Review Comments 畍ָ堣唒㷕统ךِ٦ؠؖ؎س 侧䒭ז׃ חזגְתׅ
պך椚鍑כ慧يؤ ˑ邌猰㷕˒ չ邌պָ䝤눤涸זꨇ׃ׁ God made the bulk; the surface was invented by the devil ύϦେઌੜ ェ滠 䭁侔 鍑ꨄ 䘔 膴ꨄ 䬐䭯ꆃ㾩شظ磛㶨ך邌 ˖ 鍗㯭穈䧭 ˖ ؟؎ؤװ䕎朐 磛㶨ך⡲倯 ˖ 邌ך⳽⳻ ˖ 庛䏝װ㖇⸂ 㢳㔓㶨ָꟼ
ˑ穗꿀ה˒ ٗإٓؕءؚٝؗٝ ⟎铡怴糊岀 • Genius is 1% inspiration and 99% perspiration. • There is no substitute for hard work. • I have not failed. I've just found 10,000 ways that won't work. Τδιϯେઌੜ PSˑؒآاٝ涸ז˒穗꿀锷
ˑ穗꿀ה˒ ٗإٓؕءؚٝؗٝ ⟎铡怴糊岀 銲秈ׅהչ⸕⸂֮ךהחַָֻֻׁלպה鎉גְկ ֶ̔ꆃך䫎Ⰵ➂嵲䨌遭 هأسؙװ㷕欰ך麓ꃎז⸤⫴ ד(0 • Genius is 1% inspiration and 99% perspiration. • There is no substitute for hard work. • I have not failed. I've just found 10,000 ways that won't work. Τδιϯେઌੜ PSˑؒآاٝ涸ז˒穗꿀锷
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˖ 桦 <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">AAACiXichVFNLwNRFD0dX1VfxUZi02iIVXNHBOmq0Y1lP7QkiMyMh9H5ysy0UU3/gJWdYEViIX6AH2DjD1j0J4gliY2F2+kkguBO3rzzzrvnvvPeVR1D93yiVkTq6u7p7Yv2xwYGh4ZH4qNjZc+uupooabZhu+uq4glDt0TJ131DrDuuUEzVEGtqJdveX6sJ19Nta9WvO2LLVPYsfVfXFJ+p8qZqNg6b2/EkpSiIxE8ghyCJMHJ2/A6b2IENDVWYELDgMzagwONvAzIIDnNbaDDnMtKDfYEmYqytcpbgDIXZCv/3eLURshav2zW9QK3xKQYPl5UJTNMj3dALPdAtPdH7r7UaQY22lzrPakcrnO2R44ni278qk2cf+5+qPz372MVS4FVn707AtG+hdfS1o9OXYrow3ZihK3pm/5fUonu+gVV71a7zonDxhx+VvfCLcYPk7+34CcpzKXkhRfn5ZGY5bFUUk5jCLPdjERmsIIcS1z/ACc5wLg1IsrQkpTupUiTUjONLSNkPIVKSSQ==</latexit> x <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y Ⰵ⸂ ⳿⸂ RandomForestRegressor(max_features='sqrt') <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">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</latexit> x Ⰵ⸂ <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y ⳿⸂ ֲ٦
˖ 桦 <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">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</latexit> x <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y Ⰵ⸂ ⳿⸂ ExtraTreesRegressor() <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">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</latexit> x Ⰵ⸂ <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y ⳿⸂ ֲ٦
˖ 桦 <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">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</latexit> x <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y Ⰵ⸂ ⳿⸂ GradientBoostingRegressor() <latexit sha1_base64="Nr2ImZk9Gvp+/1cBWPwAK6yswp0=">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</latexit> x Ⰵ⸂ <latexit sha1_base64="Qqfga3YaBoUI0Yb7fQVzumPP1Sw=">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</latexit> y ⳿⸂ ֲ٦
Trees (bootstrap) Neural Networks (Tanh) Linear Regression Kernel Ridge (RBF) Kernel Ridge (Laplacian) Extra Trees (no bootstrap) Gradient Boosting “ਅͷ”Ϟσϧ
Random Forest Extra Trees (bootstrap) Neural Networks (ReLU) Random Forest Extra Trees (bootstrap) Neural Networks (Tanh) Linear Regression Kernel Ridge (RBF) Kernel Ridge (Laplacian) Extra Trees (no bootstrap) Gradient Boosting
Random Forest Extra Trees (bootstrap) Neural Networks (ReLU) Random Forest Extra Trees (bootstrap) Neural Networks (Tanh) Linear Regression Kernel Ridge (RBF) Kernel Ridge (Laplacian) Extra Trees (no bootstrap) Gradient Boosting ໘ͳ͜ͱʹ͜͜ͰRashomon͕ى͖ͯ͠·͏ʂ ͜ͷΜͷϞσϧखʹೖΔࣄྫͰͷCVਫ਼ ಉϨϕϧ͕ͩςετͰͷڍಈ͍ͩͿҟͳΔʂ
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Kernel Ridge (RBF) Gradient Boosting Neural Networks (Tanh) Kernel Ridge (Laplacian) Extra Trees (no bootstrap) Neural Networks (ReLU) Random Forest Extra Trees (bootstrap)
(OCM) reactions Methane (CH4 ) is partially oxidized to C2 hydrocarbons such as ethane (C2 H6 ) and ethylene (C2 H4 ) in a single step Elemental composition of catalyst (mol%) Process parameters + Preparation Catalytic performance • Zavyalova, U.; Holena, M.; Schlögl, R.; Baerns, ChemCatChem 2011. • Followup: Kondratenko, E. V.; Schlüter, M.; Baerns, M.; Linke, D.; Holena, M. Catal. Sci. Technol. 2015. • Renalysis with Corrections & Outlier Removal Schmack, R.; Friedrich, A.; Kondratenko, E. V.; Polte, J.; Werwatz, A.; Kraehnert, R. Nat Commun 2019. 1866 catalyst records from 421 reports
bootstrap) Random Forest Extra Trees (bootstrap) sample max sample min GradientBoostingRegressor LGBMRegressor RandomForestRegressor ExtraTreesRegressor By quantile regression to .16, .5, .84 quantiles Naturally by the law of total variance bounded prediction Ԩ 寸㹀加،ٝ؟ٝـٕך✮庠ⴓ侔 ⥋걾⼒ 鎮箺ر٦ةךNBYNJOךח✮庠⦼ָֻ ךד䠐㔳׃זְ㢩䯏ٔأָؙ㼰זְ
from 421 reports (1982 - 2009) Mine, S.; Takao, M.; Yamaguchi, T.; Toyao, T.*; Maeno, Z.; Hakim Siddiki, S. M. A.; Takakusagi, S.; Shimizu, K.*; Takigawa, I.* ChemCatChem 2021. https://doi.org/10.1002/cctc.202100495. 4559 catalyst records from 542 reports The update dataset: 4559 catalyst records from 542 reports (2010 - 2019)
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