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@@ -482,11 +482,11 @@ <h2>Tentative Schedule</h2>
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<div class="schedule-item">
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<span class="schedule-time">Day 1</span>
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<ul>
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<li>09:00 Registration </li>
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<li>08:45 Registration πŸ€—. Morning talk + PhD Kitchen πŸ“š </li>
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<li class="keynote-item">
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<div class="keynote-header" onclick="toggleKeynote('keynote1')">
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<span class="keynote-toggle" id="keynote1-toggle">β–Ό</span>
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<span>09:30 Keynote 1 🎀: Sabrina Gaito</span>
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<span>09:00 Keynote 1 🎀: Sabrina Gaito</span>
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</div>
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<div class="keynote-abstract expanded" id="keynote1">
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<div
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<p>Abstract: <strong>TBA</strong> <br><br></p>
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</div>
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</li>
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<li>10:30 Coffee Break β˜•οΈ</li>
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<li class="keynote-item">
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<div class="keynote-header" onclick="toggleKeynote('keynote2')">
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<span class="keynote-toggle" id="keynote2-toggle">β–Ό</span>
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<span>10:45 Keynote 2 🎀: Davide Bacciu</span>
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</div>
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<div class="keynote-abstract expanded" id="keynote2">
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<div
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style="float: right; width: 20%; max-width: 400px; margin: 0 0 10px 20px; text-align: center;">
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<img src="/figs/news/bacciu.jpg" style="width: 100%; height: auto;" />
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</div>
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<p>Abstract: <strong>Shaping GNNs with dynamical systems</strong> <br><br>
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The dynamics of information diffusion in local message passing is a key issue that heavily
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influences graph representation learning, especially when long-range propagation is needed.
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We vouch for principled approaches that control and regulate the degree of propagation,
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conservation and dissipation of information throughout the neural flow. In the talk we
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explore some approaches stemming from a dynamical systems' view of neural networks for
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static and temporal graphs, with particular focus on wide applicability of the concepts and
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on the theoretical guarantees on information conservation.</p>
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</div>
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</li>
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<li>12:00 Lunch break 🍱 </li>
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<li>13:00 Afternoon workshops πŸ€—</li>
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<li>10:00 Coffee Break β˜•οΈ</li>
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<li class="keynote-item">
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<div class="keynote-header" onclick="toggleKeynote('keynote3')">
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<span class="keynote-toggle" id="keynote3-toggle">β–Ό</span>
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<span>13:15 Coding session 1 πŸ‘©β€πŸ’»: Veronica Lachi</span>
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<span>10:15 Coding session 1 πŸ‘©β€πŸ’»: Veronica Lachi</span>
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</div>
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<div class="keynote-abstract expanded" id="keynote3">
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<div
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with key concepts and tools.</p>
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</div>
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</li>
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<li>14:30 Coffee Break β˜•οΈ</li>
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<li>11:30 Coffee Break β˜•οΈ</li>
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<li class="keynote-item">
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<div class="keynote-header" onclick="toggleKeynote('keynote4')">
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<span class="keynote-toggle" id="keynote4-toggle">β–Ό</span>
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<span>14:45 Coding session 2 πŸ‘¨β€πŸ’»: Carlo Abate</span>
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<span>11:45 Coding session 2 πŸ‘¨β€πŸ’»: Carlo Abate</span>
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</div>
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<div class="keynote-abstract expanded" id="keynote4">
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<div
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performance.</p>
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</div>
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</li>
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<li>16:15 Break ⏸️</li>
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<li>16:30 Poster session + Pizza! πŸ•</li>
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<li>18:00 End of day 1 πŸ’€</li>
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<li>13:00 Lunch break 🍱 </li>
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<li>14:00 Afternoon talk πŸŽ™οΈ + poster session πŸ—ΊοΈ</li>
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<li class="keynote-item">
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<div class="keynote-header" onclick="toggleKeynote('keynote2')">
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<span class="keynote-toggle" id="keynote2-toggle">β–Ό</span>
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<span>14:15 Keynote 2 🎀: Davide Bacciu</span>
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</div>
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<div class="keynote-abstract expanded" id="keynote2">
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<div
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style="float: right; width: 20%; max-width: 400px; margin: 0 0 10px 20px; text-align: center;">
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<img src="/figs/news/bacciu.jpg" style="width: 100%; height: auto;" />
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</div>
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<p>Abstract: <strong>Shaping GNNs with dynamical systems</strong> <br><br>
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The dynamics of information diffusion in local message passing is a key issue that heavily
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influences graph representation learning, especially when long-range propagation is needed.
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We vouch for principled approaches that control and regulate the degree of propagation,
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conservation and dissipation of information throughout the neural flow. In the talk we
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explore some approaches stemming from a dynamical systems' view of neural networks for
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static and temporal graphs, with particular focus on wide applicability of the concepts and
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on the theoretical guarantees on information conservation.</p>
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</div>
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</li>
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<li>15:15 Break 🍎</li>
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<li>15:30 Poster session + Pizza! πŸ•</li>
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<li>17:00 End of day 1 πŸ’€</li>
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<li>20:00 Meetup social event in the city center πŸ»πŸŒƒ</li>
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</ul>
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</div>
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<div class="log-section">
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<h2>Sponsored by</h2>
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<p>
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This event is sponsored by <a href="https://www.integreat.no/" target="_blank">Integreat</a> β€” the Norwegian Centre for Knowledge-driven Machine Learning.
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This event is sponsored by <a href="https://www.integreat.no/" target="_blank">Integreat</a> β€” the Norwegian
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Centre for Knowledge-driven Machine Learning.
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</p>
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<div class="sponsor-logo" style="display: flex; align-items: center; justify-content: center; gap: 20px; margin: 30px 0;">
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<a href="https://www.integreat.no/" target="_blank" style="display: flex; align-items: center; gap: 15px; text-decoration: none;">
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<img src="/figs/events/LoG_2026/integreat-logo.png" alt="Integreat Logo" style="height: 80px; width: auto;" />
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<img src="/figs/events/LoG_2026/integreat_logo_black.png" alt="Integreat" class="integreat-text integreat-text-light" style="height: 60px; width: auto;" />
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<img src="/figs/events/LoG_2026/integreat_logo_white.png" alt="Integreat" class="integreat-text integreat-text-dark" style="height: 60px; width: auto;" />
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<div class="sponsor-logo"
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style="display: flex; align-items: center; justify-content: center; gap: 20px; margin: 30px 0;">
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<a href="https://www.integreat.no/" target="_blank"
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style="display: flex; align-items: center; gap: 15px; text-decoration: none;">
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<img src="/figs/events/LoG_2026/integreat-logo.png" alt="Integreat Logo"
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style="height: 80px; width: auto;" />
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<img src="/figs/events/LoG_2026/integreat_logo_black.png" alt="Integreat"
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class="integreat-text integreat-text-light" style="height: 60px; width: auto;" />
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<img src="/figs/events/LoG_2026/integreat_logo_white.png" alt="Integreat"
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class="integreat-text integreat-text-dark" style="height: 60px; width: auto;" />
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</a>
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</div>
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</div>

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